NITRC: The Cancer Imaging Archive (TCIA): PubMed Mentions: Display Document

PubMed Mentions

The links below are to publications on PubMed referring to The Cancer Imaging Archive (TCIA). This list is gathered weekly from PubMed automatically and was last updated on January 3, 2026.

Publication/References
A simple tool for neuroimaging data sharing. Description: Haselgrove, Christian, et al. A simple tool for neuroimaging data sharing. ''Front Neuroinform''. 2014; '''8''': 52
Automated Feature Extraction in Brain Tumor by Magnetic Resonance Imaging Using Gaussian Mixture Models. Description: Chaddad, Ahmad. Automated Feature Extraction in Brain Tumor by Magnetic Resonance Imaging Using Gaussian Mixture Models. ''Int J Biomed Imaging''. 2015; '''2015''': 868031
Comparing nonrigid registration techniques for motion corrected MR prostate diffusion imaging. Description: Buerger, C, et al. Comparing nonrigid registration techniques for motion corrected MR prostate diffusion imaging. ''Med Phys''. 2015 Jan; '''42''' (1):69-80
High-Throughput Quantification of Phenotype Heterogeneity Using Statistical Features. Description: Chaddad, Ahmad, et al. High-Throughput Quantification of Phenotype Heterogeneity Using Statistical Features. ''Adv Bioinformatics''. 2015; '''2015''': 728164
The Cancer Genome Atlas (TCGA): an immeasurable source of knowledge. Description: Tomczak, Katarzyna, et al. The Cancer Genome Atlas (TCGA): an immeasurable source of knowledge. ''Contemp Oncol (Pozn)''. 2015; '''19''' (1A):A68-77
Large scale validation of the M5L lung CAD on heterogeneous CT datasets. Description: Torres, E Lopez, et al. Large scale validation of the M5L lung CAD on heterogeneous CT datasets. ''Med Phys''. 2015 Apr; '''42''' (4):1477-89
LUNGx Challenge for computerized lung nodule classification: reflections and lessons learned. Description: Armato, Samuel G 3rd, et al. LUNGx Challenge for computerized lung nodule classification: reflections and lessons learned. ''J Med Imaging (Bellingham)''. 2015 Apr; '''2''' (2):020103
DEMARCATE: Density-based magnetic resonance image clustering for assessing tumor heterogeneity in cancer. Description: Saha, Abhijoy, et al. DEMARCATE: Density-based magnetic resonance image clustering for assessing tumor heterogeneity in cancer. ''Neuroimage Clin''. 2016; '''12''': 132-43
Publishing descriptions of non-public clinical datasets: proposed guidance for researchers, repositories, editors and funding organisations. Description: Hrynaszkiewicz, Iain, et al. Publishing descriptions of non-public clinical datasets: proposed guidance for researchers, repositories, editors and funding organisations. ''Res Integr Peer Rev''. 2016; '''1''': 6
Quantitative MRI radiomics in the prediction of molecular classifications of breast cancer subtypes in the TCGA/TCIA data set. Description: Li, Hui, et al. Quantitative MRI radiomics in the prediction of molecular classifications of breast cancer subtypes in the TCGA/TCIA data set. ''NPJ Breast Cancer''. 2016; '''2''':
Radiomics: Images Are More than Pictures, They Are Data. Description: Gillies, Robert J, et al. Radiomics: Images Are More than Pictures, They Are Data. ''Radiology''. 2016 Feb; '''278''' (2):563-77
Quantitative evaluation of robust skull stripping and tumor detection applied to axial MR images. Description: Chaddad, Ahmad, et al. Quantitative evaluation of robust skull stripping and tumor detection applied to axial MR images. ''Brain Inform''. 2016 Mar; '''3''' (1):53-61
Differential localization of glioblastoma subtype: implications on glioblastoma pathogenesis. Description: Steed, Tyler C, et al. Differential localization of glioblastoma subtype: implications on glioblastoma pathogenesis. ''Oncotarget''. 2016 May 3; '''7''' (18):24899-907
Exploring cancer genomic data from the cancer genome atlas project. Description: Lee, Ju-Seog. Exploring cancer genomic data from the cancer genome atlas project. ''BMB Rep''. 2016 Nov; '''49''' (11):607-611
An Approach Toward Automatic Classification of Tumor Histopathology of Non-Small Cell Lung Cancer Based on Radiomic Features. Description: Patil, Ravindra, et al. An Approach Toward Automatic Classification of Tumor Histopathology of Non-Small Cell Lung Cancer Based on Radiomic Features. ''Tomography''. 2016 Dec; '''2''' (4):374-377
Computational Challenges and Collaborative Projects in the NCI Quantitative Imaging Network. Description: Farahani, Keyvan, et al. Computational Challenges and Collaborative Projects in the NCI Quantitative Imaging Network. ''Tomography''. 2016 Dec; '''2''' (4):242-249
A Comprehensive Infrastructure for Big Data in Cancer Research: Accelerating Cancer Research and Precision Medicine. Description: Hinkson, Izumi V, et al. A Comprehensive Infrastructure for Big Data in Cancer Research: Accelerating Cancer Research and Precision Medicine. ''Front Cell Dev Biol''. 2017; '''5''': 83
Breast MRI radiomics: comparison of computer- and human-extracted imaging phenotypes. Description: Sutton, Elizabeth J, et al. Breast MRI radiomics: comparison of computer- and human-extracted imaging phenotypes. ''Eur Radiol Exp''. 2017; '''1''' (1):22
Effect of a computer-aided diagnosis system on radiologists' performance in grading gliomas with MRI. Description: Hsieh, Kevin Li-Chun, et al. Effect of a computer-aided diagnosis system on radiologists' performance in grading gliomas with MRI. ''PLoS One''. 2017; '''12''' (2):e0171342
A longitudinal four-dimensional computed tomography and cone beam computed tomography dataset for image-guided radiation therapy research in lung cancer. Description: Hugo, Geoffrey D, et al. A longitudinal four-dimensional computed tomography and cone beam computed tomography dataset for image-guided radiation therapy research in lung cancer. ''Med Phys''. 2017 Feb; '''44''' (2):762-771
A Population-Based Digital Reference Object (DRO) for Optimizing Dynamic Susceptibility Contrast (DSC)-MRI Methods for Clinical Trials. Description: Semmineh, Natenael B, et al. A Population-Based Digital Reference Object (DRO) for Optimizing Dynamic Susceptibility Contrast (DSC)-MRI Methods for Clinical Trials. ''Tomography''. 2017 Mar; '''3''' (1):41-49
Revealing cancer subtypes with higher-order correlations applied to imaging and omics data. Description: Graim, Kiley, et al. Revealing cancer subtypes with higher-order correlations applied to imaging and omics data. ''BMC Med Genomics''. 2017 Mar 31; '''10''' (1):20
Quality of Radiomic Features in Glioblastoma Multiforme: Impact of Semi-Automated Tumor Segmentation Software. Description: Lee, Myungeun, et al. Quality of Radiomic Features in Glioblastoma Multiforme: Impact of Semi-Automated Tumor Segmentation Software. ''Korean J Radiol''. 2017 May-Jun; '''18''' (3):498-509
Association between tumor architecture derived from generalized Q-space MRI and survival in glioblastoma. Description: Taylor, Erik N, et al. Association between tumor architecture derived from generalized Q-space MRI and survival in glioblastoma. ''Oncotarget''. 2017 Jun 27; '''8''' (26):41815-41826
Associations between gene expression profiles of invasive breast cancer and Breast Imaging Reporting and Data System MRI lexicon. Description: Kim, Ga Ram, et al. Associations between gene expression profiles of invasive breast cancer and Breast Imaging Reporting and Data System MRI lexicon. ''Ann Surg Treat Res''. 2017 Jul; '''93''' (1):18-26
Radiomic model for predicting mutations in the isocitrate dehydrogenase gene in glioblastomas. Description: Hsieh, Kevin Li-Chun, et al. Radiomic model for predicting mutations in the isocitrate dehydrogenase gene in glioblastomas. ''Oncotarget''. 2017 Jul 11; '''8''' (28):45888-45897
Radiomics strategies for risk assessment of tumour failure in head-and-neck cancer. Description: Vallieres, Martin, et al. Radiomics strategies for risk assessment of tumour failure in head-and-neck cancer. ''Sci Rep''. 2017 Aug 31; '''7''' (1):10117
Advancing The Cancer Genome Atlas glioma MRI collections with expert segmentation labels and radiomic features. Description: Bakas, Spyridon, et al. Advancing The Cancer Genome Atlas glioma MRI collections with expert segmentation labels and radiomic features. ''Sci Data''. 2017 Sep 5; '''4''': 170117
Comparison of novel multi-level Otsu (MO-PET) and conventional PET segmentation methods for measuring FDG metabolic tumor volume in patients with soft tissue sarcoma. Description: Lee, Inki, et al. Comparison of novel multi-level Otsu (MO-PET) and conventional PET segmentation methods for measuring FDG metabolic tumor volume in patients with soft tissue sarcoma. ''EJNMMI Phys''. 2017 Sep 18; '''4''' (1):22
Diffusion tensor image features predict IDH genotype in newly diagnosed WHO grade II/III gliomas. Description: Eichinger, Paul, et al. Diffusion tensor image features predict IDH genotype in newly diagnosed WHO grade II/III gliomas. ''Sci Rep''. 2017 Oct 17; '''7''' (1):13396
Predicting survival time of lung cancer patients using radiomic analysis. Description: Chaddad, Ahmad, et al. Predicting survival time of lung cancer patients using radiomic analysis. ''Oncotarget''. 2017 Nov 28; '''8''' (61):104393-104407
2D and 3D CT Radiomics Features Prognostic Performance Comparison in Non-Small Cell Lung Cancer. Description: Shen, Chen, et al. 2D and 3D CT Radiomics Features Prognostic Performance Comparison in Non-Small Cell Lung Cancer. ''Transl Oncol''. 2017 Dec; '''10''' (6):886-894
A radiomic signature as a non-invasive predictor of progression-free survival in patients with lower-grade gliomas. Description: Liu, Xing, et al. A radiomic signature as a non-invasive predictor of progression-free survival in patients with lower-grade gliomas. ''Neuroimage Clin''. 2018; '''20''': 1070-1077
Multi-faceted computational assessment of risk and progression in oligodendroglioma implicates NOTCH and PI3K pathways. Description: Halani, Sameer H, et al. Multi-faceted computational assessment of risk and progression in oligodendroglioma implicates NOTCH and PI3K pathways. ''NPJ Precis Oncol''. 2018; '''2''': 24
Quantification of glioblastoma mass effect by lateral ventricle displacement. Description: Steed, Tyler C, et al. Quantification of glioblastoma mass effect by lateral ventricle displacement. ''Sci Rep''. 2018 Feb 12; '''8''' (1):2827
Radiomics and radiogenomics for precision radiotherapy. Description: Wu, Jia, et al. Radiomics and radiogenomics for precision radiotherapy. ''J Radiat Res''. 2018 Mar 1; '''59''' (suppl_1):i25-i31
Challenges and Technological Trends Toward Improved Medical Imaging-based Predictive Data-mining. Description: Zaritsky, Assaf. Challenges and Technological Trends Toward Improved Medical Imaging-based Predictive Data-mining. ''EBioMedicine''. 2018 Sep; '''35''': 20-21
Molecular profiles of tumor contrast enhancement: A radiogenomic analysis in anaplastic gliomas. Description: Liu, Xing, et al. Molecular profiles of tumor contrast enhancement: A radiogenomic analysis in anaplastic gliomas. ''Cancer Med''. 2018 Sep; '''7''' (9):4273-4283
Magnetic resonance imaging and molecular features associated with tumor-infiltrating lymphocytes in breast cancer. Description: Wu, Jia, et al. Magnetic resonance imaging and molecular features associated with tumor-infiltrating lymphocytes in breast cancer. ''Breast Cancer Res''. 2018 Sep 3; '''20''' (1):101
Radiogenomics of lower-grade gliomas: a radiomic signature as a biological surrogate for survival prediction. Description: Qian, Zenghui, et al. Radiogenomics of lower-grade gliomas: a radiomic signature as a biological surrogate for survival prediction. ''Aging (Albany NY)''. 2018 Oct 22; '''10''' (10):2884-2899
Delta radiomic features improve prediction for lung cancer incidence: A nested case-control analysis of the National Lung Screening Trial. Description: Cherezov, Dmitry, et al. Delta radiomic features improve prediction for lung cancer incidence: A nested case-control analysis of the National Lung Screening Trial. ''Cancer Med''. 2018 Dec; '''7''' (12):6340-6356
Multiregional radiomics profiling from multiparametric MRI: Identifying an imaging predictor of IDH1 mutation status in glioblastoma. Description: Li, Zhi-Cheng, et al. Multiregional radiomics profiling from multiparametric MRI: Identifying an imaging predictor of IDH1 mutation status in glioblastoma. ''Cancer Med''. 2018 Dec; '''7''' (12):5999-6009
A Technical Review of Convolutional Neural Network-Based Mammographic Breast Cancer Diagnosis. Description: Zou, Lian, et al. A Technical Review of Convolutional Neural Network-Based Mammographic Breast Cancer Diagnosis. ''Comput Math Methods Med''. 2019; '''2019''': 6509357
Immune Cytolytic Activity Is Associated With Genetic and Clinical Properties of Glioma. Description: Wang, Zhi-Liang, et al. Immune Cytolytic Activity Is Associated With Genetic and Clinical Properties of Glioma. ''Front Immunol''. 2019; '''10''': 1756
Performance of sparse-view CT reconstruction with multi-directional gradient operators. Description: Hsieh, Chia-Jui, et al. Performance of sparse-view CT reconstruction with multi-directional gradient operators. ''PLoS One''. 2019; '''14''' (1):e0209674
Discovery of pre-therapy 2-deoxy-2-(18)F-fluoro-D-glucose positron emission tomography-based radiomics classifiers of survival outcome in non-small-cell lung cancer patients. Description: Arshad, Mubarik A, et al. Discovery of pre-therapy 2-deoxy-2-(18)F-fluoro-D-glucose positron emission tomography-based radiomics classifiers of survival outcome in non-small-cell lung cancer patients. ''Eur J Nucl Med Mol Imaging''. 2019 Feb; '''46''' (2):455-466
A mathematical-descriptor of tumor-mesoscopic-structure from computed-tomography images annotates prognostic- and molecular-phenotypes of epithelial ovarian cancer. Description: Lu, Haonan, et al. A mathematical-descriptor of tumor-mesoscopic-structure from computed-tomography images annotates prognostic- and molecular-phenotypes of epithelial ovarian cancer. ''Nat Commun''. 2019 Feb 15; '''10''' (1):764
QIN Benchmarks for Clinical Translation of Quantitative Imaging Tools. Description: Farahani, Keyvan, et al. QIN Benchmarks for Clinical Translation of Quantitative Imaging Tools. ''Tomography''. 2019 Mar; '''5''' (1):1-6
Acute Tumor Transition Angle on Computed Tomography Predicts Chromosomal Instability Status of Primary Gastric Cancer: Radiogenomics Analysis from TCGA and Independent Validation. Description: Lai, Ying-Chieh, et al. Acute Tumor Transition Angle on Computed Tomography Predicts Chromosomal Instability Status of Primary Gastric Cancer: Radiogenomics Analysis from TCGA and Independent Validation. ''Cancers (Basel)''. 2019 May 9; '''11''' (5):
Differentiation of glioblastoma from solitary brain metastases using radiomic machine-learning classifiers. Description: Qian, Zenghui, et al. Differentiation of glioblastoma from solitary brain metastases using radiomic machine-learning classifiers. ''Cancer Lett''. 2019 Jun 1; '''451''': 128-135
A survey and evaluation of Web-based tools/databases for variant analysis of TCGA data. Description: Zhang, Zhuo, et al. A survey and evaluation of Web-based tools/databases for variant analysis of TCGA data. ''Brief Bioinform''. 2019 Jul 19; '''20''' (4):1524-1541
Advanced 3D printed model of middle cerebral artery aneurysms for neurosurgery simulation. Description: Nagassa, Ruth G, et al. Advanced 3D printed model of middle cerebral artery aneurysms for neurosurgery simulation. ''3D Print Med''. 2019 Aug 1; '''5''' (1):11
Tumor Transcriptome Reveals High Expression of IL-8 in Non-Small Cell Lung Cancer Patients with Low Pectoralis Muscle Area and Reduced Survival. Description: Cury, Sarah Santiloni, et al. Tumor Transcriptome Reveals High Expression of IL-8 in Non-Small Cell Lung Cancer Patients with Low Pectoralis Muscle Area and Reduced Survival. ''Cancers (Basel)''. 2019 Aug 26; '''11''' (9):
Tumour heterogeneity revealed by unsupervised decomposition of dynamic contrast-enhanced magnetic resonance imaging is associated with underlying gene expression patterns and poor survival in breast cancer patients. Description: Fan, Ming, et al. Tumour heterogeneity revealed by unsupervised decomposition of dynamic contrast-enhanced magnetic resonance imaging is associated with underlying gene expression patterns and poor survival in breast cancer patients. ''Breast Cancer Res''. 2019 Oct 17; '''21''' (1):112
Distributed radiomics as a signature validation study using the Personal Health Train infrastructure. Description: Shi, Zhenwei, et al. Distributed radiomics as a signature validation study using the Personal Health Train infrastructure. ''Sci Data''. 2019 Oct 22; '''6''' (1):218
Are shape morphologies associated with survival? A potential shape-based biomarker predicting survival in lung cancer. Description: Saad, Maliazurina, et al. Are shape morphologies associated with survival? A potential shape-based biomarker predicting survival in lung cancer. ''J Cancer Res Clin Oncol''. 2019 Dec; '''145''' (12):2937-2950
Fusion Radiomics Features from Conventional MRI Predict MGMT Promoter Methylation Status in Lower Grade Gliomas. Description: Jiang, Chendan, et al. Fusion Radiomics Features from Conventional MRI Predict MGMT Promoter Methylation Status in Lower Grade Gliomas. ''Eur J Radiol''. 2019 Dec; '''121''': 108714
Integrative Models of Histopathological Image Features and Omics Data Predict Survival in Head and Neck Squamous Cell Carcinoma. Description: Zeng, Hao, et al. Integrative Models of Histopathological Image Features and Omics Data Predict Survival in Head and Neck Squamous Cell Carcinoma. ''Front Cell Dev Biol''. 2020; '''8''': 553099
Machine Learning Based on a Multiparametric and Multiregional Radiomics Signature Predicts Radiotherapeutic Response in Patients with Glioblastoma. Description: Pan, Zi-Qi, et al. Machine Learning Based on a Multiparametric and Multiregional Radiomics Signature Predicts Radiotherapeutic Response in Patients with Glioblastoma. ''Behav Neurol''. 2020; '''2020''': 1712604
Stemness Related Genes Revealed by Network Analysis Associated With Tumor Immune Microenvironment and the Clinical Outcome in Lung Adenocarcinoma. Description: Zeng, Hao, et al. Stemness Related Genes Revealed by Network Analysis Associated With Tumor Immune Microenvironment and the Clinical Outcome in Lung Adenocarcinoma. ''Front Genet''. 2020; '''11''': 549213
Automatic Prediction of MGMT Status in Glioblastoma via Deep Learning-Based MR Image Analysis. Description: Chen, Xin, et al. Automatic Prediction of MGMT Status in Glioblastoma via Deep Learning-Based MR Image Analysis. ''Biomed Res Int''. 2020; '''2020''': 9258649
Deciphering the tumor microenvironment through radiomics in non-small cell lung cancer: Correlation with immune profiles. Description: Yoon, Hyun Jung, et al. Deciphering the tumor microenvironment through radiomics in non-small cell lung cancer: Correlation with immune profiles. ''PLoS One''. 2020; '''15''' (4):e0231227
Development and Validation of Pre- and Post-Operative Models to Predict Recurrence After Resection of Solitary Hepatocellular Carcinoma: A Multi-Institutional Study. Description: Wu, Ming-Yu, et al. Development and Validation of Pre- and Post-Operative Models to Predict Recurrence After Resection of Solitary Hepatocellular Carcinoma: A Multi-Institutional Study. ''Cancer Manag Res''. 2020; '''12''': 3503-3512
Identifying BAP1 Mutations in Clear-Cell Renal Cell Carcinoma by CT Radiomics: Preliminary Findings. Description: Feng, Zhan, et al. Identifying BAP1 Mutations in Clear-Cell Renal Cell Carcinoma by CT Radiomics: Preliminary Findings. ''Front Oncol''. 2020; '''10''': 279
Radiomics Features Predict CIC Mutation Status in Lower Grade Glioma. Description: Zhang, Luyuan, et al. Radiomics Features Predict CIC Mutation Status in Lower Grade Glioma. ''Front Oncol''. 2020; '''10''': 937
Segmentation and Classification in Digital Pathology for Glioma Research: Challenges and Deep Learning Approaches. Description: Kurc, Tahsin, et al. Segmentation and Classification in Digital Pathology for Glioma Research: Challenges and Deep Learning Approaches. ''Front Neurosci''. 2020; '''14''': 27
Computer-aided diagnosis of isocitrate dehydrogenase genotypes in glioblastomas from radiomic patterns. Description: Lo, Chung-Ming, et al. Computer-aided diagnosis of isocitrate dehydrogenase genotypes in glioblastomas from radiomic patterns. ''Medicine (Baltimore)''. 2020 Feb; '''99''' (8):e19123
SlicerDMRI: Diffusion MRI and Tractography Research Software for Brain Cancer Surgery Planning and Visualization. Description: Zhang, Fan, et al. SlicerDMRI: Diffusion MRI and Tractography Research Software for Brain Cancer Surgery Planning and Visualization. ''JCO Clin Cancer Inform''. 2020 Mar; '''4''': 299-309
From Medical Imaging to Radiomics: Role of Data Science for Advancing Precision Health. Description: Capobianco, Enrico, et al. From Medical Imaging to Radiomics: Role of Data Science for Advancing Precision Health. ''J Pers Med''. 2020 Mar 2; '''10''' (1):
Data-driven translational prostate cancer research: from biomarker discovery to clinical decision. Description: Lin, Yuxin, et al. Data-driven translational prostate cancer research: from biomarker discovery to clinical decision. ''J Transl Med''. 2020 Mar 7; '''18''' (1):119
Artificial intelligence in oncology. Description: Shimizu, Hideyuki, et al. Artificial intelligence in oncology. ''Cancer Sci''. 2020 May; '''111''' (5):1452-1460
Weakly-supervised learning for lung carcinoma classification using deep learning. Description: Kanavati, Fahdi, et al. Weakly-supervised learning for lung carcinoma classification using deep learning. ''Sci Rep''. 2020 Jun 9; '''10''' (1):9297
AI in Medical Imaging Informatics: Current Challenges and Future Directions. Description: Panayides, Andreas S, et al. AI in Medical Imaging Informatics: Current Challenges and Future Directions. ''IEEE J Biomed Health Inform''. 2020 Jul; '''24''' (7):1837-1857
Surgical spectral imaging. Description: Clancy, Neil T, et al. Surgical spectral imaging. ''Med Image Anal''. 2020 Jul; '''63''': 101699
Open Data Revolution in Clinical Research: Opportunities and Challenges. Description: Shahin, Mohamed H, et al. Open Data Revolution in Clinical Research: Opportunities and Challenges. ''Clin Transl Sci''. 2020 Jul; '''13''' (4):665-674
Radiomics for lung adenocarcinoma manifesting as pure ground-glass nodules: invasive prediction. Description: Sun, Yingli, et al. Radiomics for lung adenocarcinoma manifesting as pure ground-glass nodules: invasive prediction. ''Eur Radiol''. 2020 Jul; '''30''' (7):3650-3659
Radiomics-based prediction of survival in patients with head and neck squamous cell carcinoma based on pre- and post-treatment (18)F-PET/CT. Description: Liu, Zheran, et al. Radiomics-based prediction of survival in patients with head and neck squamous cell carcinoma based on pre- and post-treatment (18)F-PET/CT. ''Aging (Albany NY)''. 2020 Jul 16; '''12''' (14):14593-14619
Multi-view secondary input collaborative deep learning for lung nodule 3D segmentation. Description: Dong, Xianling, et al. Multi-view secondary input collaborative deep learning for lung nodule 3D segmentation. ''Cancer Imaging''. 2020 Aug 1; '''20''' (1):53
Single-Cell Spatial Analysis of Tumor and Immune Microenvironment on Whole-Slide Image Reveals Hepatocellular Carcinoma Subtypes. Description: Wang, Haiyue, et al. Single-Cell Spatial Analysis of Tumor and Immune Microenvironment on Whole-Slide Image Reveals Hepatocellular Carcinoma Subtypes. ''Cancers (Basel)''. 2020 Nov 28; '''12''' (12):
Age-related copy number variations and expression levels of F-box protein FBXL20 predict ovarian cancer prognosis. Description: Zheng, Shuhua, et al. Age-related copy number variations and expression levels of F-box protein FBXL20 predict ovarian cancer prognosis. ''Transl Oncol''. 2020 Dec; '''13''' (12):100863
Radiomic features based on Hessian index for prediction of prognosis in head-and-neck cancer patients. Description: Le, Quoc Cuong, et al. Radiomic features based on Hessian index for prediction of prognosis in head-and-neck cancer patients. ''Sci Rep''. 2020 Dec 4; '''10''' (1):21301
Deep learning-based cross-classifications reveal conserved spatial behaviors within tumor histological images. Description: Noorbakhsh, Javad, et al. Deep learning-based cross-classifications reveal conserved spatial behaviors within tumor histological images. ''Nat Commun''. 2020 Dec 11; '''11''' (1):6367
A partial encryption algorithm for medical images based on quick response code and reversible data hiding technology. Description: Li, Jian, et al. A partial encryption algorithm for medical images based on quick response code and reversible data hiding technology. ''BMC Med Inform Decis Mak''. 2020 Dec 15; '''20''' (Suppl 14):297
Artificial intelligence in the diagnosis of COVID-19: challenges and perspectives. Description: Huang, Shigao, et al. Artificial intelligence in the diagnosis of COVID-19: challenges and perspectives. ''Int J Biol Sci''. 2021; '''17''' (6):1581-1587
A Voxel-Based Radiographic Analysis Reveals the Biological Character of Proneural-Mesenchymal Transition in Glioblastoma. Description: Qi, Tengfei, et al. A Voxel-Based Radiographic Analysis Reveals the Biological Character of Proneural-Mesenchymal Transition in Glioblastoma. ''Front Oncol''. 2021; '''11''': 595259
DeepDicomSort: An Automatic Sorting Algorithm for Brain Magnetic Resonance Imaging Data. Description: van der Voort, Sebastian R, et al. DeepDicomSort: An Automatic Sorting Algorithm for Brain Magnetic Resonance Imaging Data. ''Neuroinformatics''. 2021 Jan; '''19''' (1):159-184
Deep Learning in Cancer Diagnosis and Prognosis Prediction: A Minireview on Challenges, Recent Trends, and Future Directions. Description: Tufail, Ahsan Bin, et al. Deep Learning in Cancer Diagnosis and Prognosis Prediction: A Minireview on Challenges, Recent Trends, and Future Directions. ''Comput Math Methods Med''. 2021; '''2021''': 9025470
Deep Learning Radiomics to Predict PTEN Mutation Status From Magnetic Resonance Imaging in Patients With Glioma. Description: Chen, Hongyu, et al. Deep Learning Radiomics to Predict PTEN Mutation Status From Magnetic Resonance Imaging in Patients With Glioma. ''Front Oncol''. 2021; '''11''': 734433
Development and Validation of a Radiomic Nomogram for Predicting the Prognosis of Kidney Renal Clear Cell Carcinoma. Description: Gao, Ruizhi, et al. Development and Validation of a Radiomic Nomogram for Predicting the Prognosis of Kidney Renal Clear Cell Carcinoma. ''Front Oncol''. 2021; '''11''': 613668
Exploration of an Integrative Prognostic Model of Radiogenomics Features With Underlying Gene Expression Patterns in Clear Cell Renal Cell Carcinoma. Description: Huang, Yeqian, et al. Exploration of an Integrative Prognostic Model of Radiogenomics Features With Underlying Gene Expression Patterns in Clear Cell Renal Cell Carcinoma. ''Front Oncol''. 2021; '''11''': 640881
Imaging-Genomics in Glioblastoma: Combining Molecular and Imaging Signatures. Description: Liu, Dongming, et al. Imaging-Genomics in Glioblastoma: Combining Molecular and Imaging Signatures. ''Front Oncol''. 2021; '''11''': 699265
Integrative Analysis of Histopathological Images and Genomic Data in Colon Adenocarcinoma. Description: Li, Hui, et al. Integrative Analysis of Histopathological Images and Genomic Data in Colon Adenocarcinoma. ''Front Oncol''. 2021; '''11''': 636451
Investigation of Genetic Determinants of Glioma Immune Phenotype by Integrative Immunogenomic Scale Analysis. Description: Zhao, Binghao, et al. Investigation of Genetic Determinants of Glioma Immune Phenotype by Integrative Immunogenomic Scale Analysis. ''Front Immunol''. 2021; '''12''': 557994
Lesion covariance networks reveal proposed origins and pathways of diffuse gliomas. Description: Mandal, Ayan S, et al. Lesion covariance networks reveal proposed origins and pathways of diffuse gliomas. ''Brain Commun''. 2021; '''3''' (4):fcab289
Multimodal Deep Learning for Prognosis Prediction in Renal Cancer. Description: Schulz, Stefan, et al. Multimodal Deep Learning for Prognosis Prediction in Renal Cancer. ''Front Oncol''. 2021; '''11''': 788740
Multiparametric MRI Features Predict the SYP Gene Expression in Low-Grade Glioma Patients: A Machine Learning-Based Radiomics Analysis. Description: Xiao, Zheng, et al. Multiparametric MRI Features Predict the SYP Gene Expression in Low-Grade Glioma Patients: A Machine Learning-Based Radiomics Analysis. ''Front Oncol''. 2021; '''11''': 663451
Radiomics and Digital Image Texture Analysis in Oncology (Review). Description: Litvin, A A, et al. Radiomics and Digital Image Texture Analysis in Oncology (Review). ''Sovrem Tekhnologii Med''. 2021; '''13''' (2):97-104
The Prognostic Value of Radiomics Features Extracted From Computed Tomography in Patients With Localized Clear Cell Renal Cell Carcinoma After Nephrectomy. Description: Tang, Xin, et al. The Prognostic Value of Radiomics Features Extracted From Computed Tomography in Patients With Localized Clear Cell Renal Cell Carcinoma After Nephrectomy. ''Front Oncol''. 2021; '''11''': 591502
Uncovering a Distinct Gene Signature in Endothelial Cells Associated With Contrast Enhancement in Glioblastoma. Description: Yang, Fan, et al. Uncovering a Distinct Gene Signature in Endothelial Cells Associated With Contrast Enhancement in Glioblastoma. ''Front Oncol''. 2021; '''11''': 683367
A Systematic Approach of Data Collection and Analysis in Medical Imaging Research. Description: K N, Manjunath, et al. A Systematic Approach of Data Collection and Analysis in Medical Imaging Research. ''Asian Pac J Cancer Prev''. 2021 Feb 1; '''22''' (2):537-546
Genetic alterations associated with (18)F-fluorodeoxyglucose positron emission tomography/computed tomography in head and neck squamous cell carcinoma. Description: Han, Sangwon, et al. Genetic alterations associated with (18)F-fluorodeoxyglucose positron emission tomography/computed tomography in head and neck squamous cell carcinoma. ''Transl Oncol''. 2021 Feb; '''14''' (2):100988
Multi-modal magnetic resonance imaging-based grading analysis for gliomas by integrating radiomics and deep features. Description: Ning, Zhenyuan, et al. Multi-modal magnetic resonance imaging-based grading analysis for gliomas by integrating radiomics and deep features. ''Ann Transl Med''. 2021 Feb; '''9''' (4):298
Current limitations to identify COVID-19 using artificial intelligence with chest X-ray imaging. Description: Lopez-Cabrera, Jose Daniel, et al. Current limitations to identify COVID-19 using artificial intelligence with chest X-ray imaging. ''Health Technol (Berl)''. 2021 Feb 5; 1-14
Generalized chest CT and lab curves throughout the course of COVID-19. Description: Kassin, Michael T, et al. Generalized chest CT and lab curves throughout the course of COVID-19. ''Sci Rep''. 2021 Mar 25; '''11''' (1):6940
Integrative radiogenomics analysis for predicting molecular features and survival in clear cell renal cell carcinoma. Description: Zeng, Hao, et al. Integrative radiogenomics analysis for predicting molecular features and survival in clear cell renal cell carcinoma. ''Aging (Albany NY)''. 2021 Mar 26; '''13''' (7):9960-9975
Radiomics for precision medicine: Current challenges, future prospects, and the proposal of a new framework. Description: Ibrahim, A, et al. Radiomics for precision medicine: Current challenges, future prospects, and the proposal of a new framework. ''Methods''. 2021 Apr; '''188''': 20-29
The next horizon in precision oncology: Proteogenomics to inform cancer diagnosis and treatment. Description: Rodriguez, Henry, et al. The next horizon in precision oncology: Proteogenomics to inform cancer diagnosis and treatment. ''Cell''. 2021 Apr 1; '''184''' (7):1661-1670
Radiomic profiling of clear cell renal cell carcinoma reveals subtypes with distinct prognoses and molecular pathways. Description: Lin, Peng, et al. Radiomic profiling of clear cell renal cell carcinoma reveals subtypes with distinct prognoses and molecular pathways. ''Transl Oncol''. 2021 Apr 13; '''14''' (7):101078
CT and MRI radiomics of bone and soft-tissue sarcomas: a systematic review of reproducibility and validation strategies. Description: Gitto, Salvatore, et al. CT and MRI radiomics of bone and soft-tissue sarcomas: a systematic review of reproducibility and validation strategies. ''Insights Imaging''. 2021 Jun 2; '''12''' (1):68
Geometric and dosimetric impact of 3D generative adversarial network-based metal artifact reduction algorithm on VMAT and IMPT for the head and neck region. Description: Nakamura, Mitsuhiro, et al. Geometric and dosimetric impact of 3D generative adversarial network-based metal artifact reduction algorithm on VMAT and IMPT for the head and neck region. ''Radiat Oncol''. 2021 Jun 6; '''16''' (1):96
Deep learning for end-to-end kidney cancer diagnosis on multi-phase abdominal computed tomography. Description: Uhm, Kwang-Hyun, et al. Deep learning for end-to-end kidney cancer diagnosis on multi-phase abdominal computed tomography. ''NPJ Precis Oncol''. 2021 Jun 18; '''5''' (1):54
Deep learning for semi-automated unidirectional measurement of lung tumor size in CT. Description: Woo, MinJae, et al. Deep learning for semi-automated unidirectional measurement of lung tumor size in CT. ''Cancer Imaging''. 2021 Jun 23; '''21''' (1):43
Histopathological image and gene expression pattern analysis for predicting molecular features and prognosis of head and neck squamous cell carcinoma. Description: Chen, Linyan, et al. Histopathological image and gene expression pattern analysis for predicting molecular features and prognosis of head and neck squamous cell carcinoma. ''Cancer Med''. 2021 Jul; '''10''' (13):4615-4628
Radiomic assessment as a method for predicting tumor mutation burden (TMB) of bladder cancer patients: a feasibility study. Description: Tang, Xin, et al. Radiomic assessment as a method for predicting tumor mutation burden (TMB) of bladder cancer patients: a feasibility study. ''BMC Cancer''. 2021 Jul 16; '''21''' (1):823
Quantitative evaluation of deep convolutional neural network-based image denoising for low-dose computed tomography. Description: Usui, Keisuke, et al. Quantitative evaluation of deep convolutional neural network-based image denoising for low-dose computed tomography. ''Vis Comput Ind Biomed Art''. 2021 Jul 25; '''4''' (1):21
A Generalized Linear modeling approach to bootstrapping multi-frame PET image data. Description: O'Sullivan, Finbarr, et al. A Generalized Linear modeling approach to bootstrapping multi-frame PET image data. ''Med Image Anal''. 2021 Aug; '''72''': 102132
Comparison of Supervised and Unsupervised Approaches for the Generation of Synthetic CT from Cone-Beam CT. Description: Rossi, Matteo, et al. Comparison of Supervised and Unsupervised Approaches for the Generation of Synthetic CT from Cone-Beam CT. ''Diagnostics (Basel)''. 2021 Aug 9; '''11''' (8):
Text-based multi-dimensional medical images retrieval according to the features-usage correlation. Description: Safaei, AliAsghar. Text-based multi-dimensional medical images retrieval according to the features-usage correlation. ''Med Biol Eng Comput''. 2021 Aug 20;
Radiological tumor classification across imaging modality and histology. Description: Wu, Jia, et al. Radiological tumor classification across imaging modality and histology. ''Nat Mach Intell''. 2021 Sep; '''3''': 787-798
Integration of histopathological images and multi-dimensional omics analyses predicts molecular features and prognosis in high-grade serous ovarian cancer. Description: Zeng, Hao, et al. Integration of histopathological images and multi-dimensional omics analyses predicts molecular features and prognosis in high-grade serous ovarian cancer. ''Gynecol Oncol''. 2021 Oct; '''163''' (1):171-180
Overall Survival Prediction in Renal Cell Carcinoma Patients Using Computed Tomography Radiomic and Clinical Information. Description: Khodabakhshi, Zahra, et al. Overall Survival Prediction in Renal Cell Carcinoma Patients Using Computed Tomography Radiomic and Clinical Information. ''J Digit Imaging''. 2021 Oct; '''34''' (5):1086-1098
A Combined Radiomics and Machine Learning Approach to Distinguish Clinically Significant Prostate Lesions on a Publicly Available MRI Dataset. Description: Donisi, Leandro, et al. A Combined Radiomics and Machine Learning Approach to Distinguish Clinically Significant Prostate Lesions on a Publicly Available MRI Dataset. ''J Imaging''. 2021 Oct 18; '''7''' (10):
Image-based shading correction for narrow-FOV truncated pelvic CBCT with deep convolutional neural networks and transfer learning. Description: Rossi, Matteo, et al. Image-based shading correction for narrow-FOV truncated pelvic CBCT with deep convolutional neural networks and transfer learning. ''Med Phys''. 2021 Nov; '''48''' (11):7112-7126
Machine intelligence in non-invasive endocrine cancer diagnostics. Description: Thomasian, Nicole M, et al. Machine intelligence in non-invasive endocrine cancer diagnostics. ''Nat Rev Endocrinol''. 2021 Nov 9;
Explainable Artificial Intelligence for Human-Machine Interaction in Brain Tumor Localization. Description: Esmaeili, Morteza, et al. Explainable Artificial Intelligence for Human-Machine Interaction in Brain Tumor Localization. ''J Pers Med''. 2021 Nov 16; '''11''' (11):
Applications of Radiomics and Radiogenomics in High-Grade Gliomas in the Era of Precision Medicine. Description: Fathi Kazerooni, Anahita, et al. Applications of Radiomics and Radiogenomics in High-Grade Gliomas in the Era of Precision Medicine. ''Cancers (Basel)''. 2021 Nov 25; '''13''' (23):
A multi-object deep neural network architecture to detect prostate anatomy in T2-weighted MRI: Performance evaluation. Description: Baldeon-Calisto, Maria, et al. A multi-object deep neural network architecture to detect prostate anatomy in T2-weighted MRI: Performance evaluation. ''Front Nucl Med''. 2022; '''2''': 1083245
Development and Validation of an MRI Radiomics-Based Signature to Predict Histological Grade in Patients with Invasive Breast Cancer. Description: Wang, Shihui, et al. Development and Validation of an MRI Radiomics-Based Signature to Predict Histological Grade in Patients with Invasive Breast Cancer. ''Breast Cancer (Dove Med Press)''. 2022; '''14''': 335-342
Multimodal analysis suggests differential immuno-metabolic crosstalk in lung squamous cell carcinoma and adenocarcinoma. Description: Leitner, Brooks P, et al. Multimodal analysis suggests differential immuno-metabolic crosstalk in lung squamous cell carcinoma and adenocarcinoma. ''NPJ Precis Oncol''. 2022 Jan 27; '''6''' (1):8
An artificial intelligence method to assess the tumor microenvironment with treatment outcomes for gastric cancer patients after gastrectomy. Description: Chen, Tao, et al. An artificial intelligence method to assess the tumor microenvironment with treatment outcomes for gastric cancer patients after gastrectomy. ''J Transl Med''. 2022 Feb 21; '''20''' (1):100
A deep learning pipeline to simulate fluorodeoxyglucose (FDG) uptake in head and neck cancers using non-contrast CT images without the administration of radioactive tracer. Description: Chandrashekar, Anirudh, et al. A deep learning pipeline to simulate fluorodeoxyglucose (FDG) uptake in head and neck cancers using non-contrast CT images without the administration of radioactive tracer. ''Insights Imaging''. 2022 Mar 14; '''13''' (1):45
Quantifying lung cancer heterogeneity using novel CT features: a cross-institute study. Description: Wang, Zixing, et al. Quantifying lung cancer heterogeneity using novel CT features: a cross-institute study. ''Insights Imaging''. 2022 Apr 28; '''13''' (1):82
HFCF-Net: A hybrid-feature cross fusion network for COVID-19 lesion segmentation from CT volumetric images. Description: Wang, Yanting, et al. HFCF-Net: A hybrid-feature cross fusion network for COVID-19 lesion segmentation from CT volumetric images. ''Med Phys''. 2022 Jun; '''49''' (6):3797-3815
Deep learning features encode interpretable morphologies within histological images. Description: Foroughi Pour, Ali, et al. Deep learning features encode interpretable morphologies within histological images. ''Sci Rep''. 2022 Jun 8; '''12''' (1):9428
Prognostic impact of an integrative analysis of [(18)F]FDG PET parameters and infiltrating immune cell scores in lung adenocarcinoma. Description: Choi, Jinyeong, et al. Prognostic impact of an integrative analysis of [(18)F]FDG PET parameters and infiltrating immune cell scores in lung adenocarcinoma. ''EJNMMI Res''. 2022 Jun 27; '''12''' (1):38
Association testing for binary trees-A Markov branching process approach. Description: Wu, Xiaowei, et al. Association testing for binary trees-A Markov branching process approach. ''Stat Med''. 2022 Jun 30; '''41''' (14):2557-2573
Development and verification of radiomics framework for computed tomography image segmentation. Description: Gu, Jiabing, et al. Development and verification of radiomics framework for computed tomography image segmentation. ''Med Phys''. 2022 Oct; '''49''' (10):6527-6537
Patient-Specific Magnetic Catheters for Atraumatic Autonomous Endoscopy. Description: Pittiglio, Giovanni, et al. Patient-Specific Magnetic Catheters for Atraumatic Autonomous Endoscopy. ''Soft Robot''. 2022 Dec; '''9''' (6):1120-1133
The diagnosis, classification, and treatment of sarcoma in this era of artificial intelligence and immunotherapy. Description: Crombe, Amandine, et al. The diagnosis, classification, and treatment of sarcoma in this era of artificial intelligence and immunotherapy. ''Cancer Commun (Lond)''. 2022 Dec; '''42''' (12):1288-1313
An intravenous pancreatic cancer therapeutic: Characterization of CRISPR/Cas9n-modified Clostridium novyi-Non Toxic. Description: Dailey, Kaitlin M, et al. An intravenous pancreatic cancer therapeutic: Characterization of CRISPR/Cas9n-modified Clostridium novyi-Non Toxic. ''PLoS One''. 2023; '''18''' (11):e0289183
Comparison of MRI radiomics-based machine learning survival models in predicting prognosis of glioblastoma multiforme. Description: Zhang, Di, et al. Comparison of MRI radiomics-based machine learning survival models in predicting prognosis of glioblastoma multiforme. ''Front Med (Lausanne)''. 2023; '''10''': 1271687
CT radiomics for noninvasively predicting NQO1 expression levels in hepatocellular carcinoma. Description: He, Zenglei, et al. CT radiomics for noninvasively predicting NQO1 expression levels in hepatocellular carcinoma. ''PLoS One''. 2023; '''18''' (9):e0290900
Deep learning prediction of pathological complete response, residual cancer burden, and progression-free survival in breast cancer patients. Description: Dammu, Hongyi, et al. Deep learning prediction of pathological complete response, residual cancer burden, and progression-free survival in breast cancer patients. ''PLoS One''. 2023; '''18''' (1):e0280148
Med-ImageTools: An open-source Python package for robust data processing pipelines and curating medical imaging data. Description: Kim, Sejin, et al. Med-ImageTools: An open-source Python package for robust data processing pipelines and curating medical imaging data. ''F1000Res''. 2023; '''12''': 118
SIFT-GVF-based lung edge correction method for correcting the lung region in CT images. Description: Li, Xin, et al. SIFT-GVF-based lung edge correction method for correcting the lung region in CT images. ''PLoS One''. 2023; '''18''' (2):e0282107
The involvement of brain regions associated with lower KPS and shorter survival time predicts a poor prognosis in glioma. Description: Bao, Hongbo, et al. The involvement of brain regions associated with lower KPS and shorter survival time predicts a poor prognosis in glioma. ''Front Neurol''. 2023; '''14''': 1264322
Translating Data Science Results into Precision Oncology Decisions: A Mini Review. Description: Capobianco, Enrico, et al. Translating Data Science Results into Precision Oncology Decisions: A Mini Review. ''J Clin Med''. 2023 Jan 5; '''12''' (2):
Molecular hallmarks of breast multiparametric magnetic resonance imaging during neoadjuvant chemotherapy. Description: Lin, Peng, et al. Molecular hallmarks of breast multiparametric magnetic resonance imaging during neoadjuvant chemotherapy. ''Radiol Med''. 2023 Jan 21; 1-13
Radiogenomic association of deep MR imaging features with genomic profiles and clinical characteristics in breast cancer. Description: Liu, Qian, et al. Radiogenomic association of deep MR imaging features with genomic profiles and clinical characteristics in breast cancer. ''Biomark Res''. 2023 Jan 24; '''11''' (1):9
Prognostic value of (18)F-FDG PET/CT-based radiomics combining dosiomics and dose volume histogram for head and neck cancer. Description: Wang, Bingzhen, et al. Prognostic value of (18)F-FDG PET/CT-based radiomics combining dosiomics and dose volume histogram for head and neck cancer. ''EJNMMI Res''. 2023 Feb 13; '''13''' (1):14
Computed tomography-based radiomics prediction of CTLA4 expression and prognosis in clear cell renal cell carcinoma. Description: He, Hongchao, et al. Computed tomography-based radiomics prediction of CTLA4 expression and prognosis in clear cell renal cell carcinoma. ''Cancer Med''. 2023 Mar; '''12''' (6):7627-7638
New insights into glioma frequency maps: From genetic and transcriptomic correlate to survival prediction. Description: Bao, Hongbo, et al. New insights into glioma frequency maps: From genetic and transcriptomic correlate to survival prediction. ''Int J Cancer''. 2023 Mar 1; '''152''' (5):998-1012
Fully-automated sarcopenia assessment in head and neck cancer: development and external validation of a deep learning pipeline. Description: Ye, Zezhong, et al. Fully-automated sarcopenia assessment in head and neck cancer: development and external validation of a deep learning pipeline. ''medRxiv''. 2023 Mar 6;
An Online Mammography Database with Biopsy Confirmed Types. Description: Cai, Hongmin, et al. An Online Mammography Database with Biopsy Confirmed Types. ''Sci Data''. 2023 Mar 7; '''10''' (1):123
Direct prediction of Homologous Recombination Deficiency from routine histology in ten different tumor types with attention-based Multiple Instance Learning: a development and validation study. Description: Lavinia Loeffler, Chiara Maria, et al. Direct prediction of Homologous Recombination Deficiency from routine histology in ten different tumor types with attention-based Multiple Instance Learning: a development and validation study. ''medRxiv''. 2023 Mar 10;
An immune indicator based on BTK and DPEP2 identifies hot and cold tumors and clinical treatment outcomes in lung adenocarcinoma. Description: Han, Tao, et al. An immune indicator based on BTK and DPEP2 identifies hot and cold tumors and clinical treatment outcomes in lung adenocarcinoma. ''Sci Rep''. 2023 Mar 29; '''13''' (1):5153
MTF1 has the potential as a diagnostic and prognostic marker for gastric cancer and is associated with good prognosis. Description: He, Jin, et al. MTF1 has the potential as a diagnostic and prognostic marker for gastric cancer and is associated with good prognosis. ''Clin Transl Oncol''. 2023 Apr 24; 1-11
Clinical applications of artificial intelligence in radiology. Description: Mello-Thoms, Claudia, et al. Clinical applications of artificial intelligence in radiology. ''Br J Radiol''. 2023 Apr 26; '''96''' (1150):20221031
Comparison and fusion prediction model for lung adenocarcinoma with micropapillary and solid pattern using clinicoradiographic, radiomics and deep learning features. Description: Wang, Fen, et al. Comparison and fusion prediction model for lung adenocarcinoma with micropapillary and solid pattern using clinicoradiographic, radiomics and deep learning features. ''Sci Rep''. 2023 Jun 8; '''13''' (1):9302
Assessment of brain cancer atlas maps with multimodal imaging features. Description: Capobianco, Enrico, et al. Assessment of brain cancer atlas maps with multimodal imaging features. ''J Transl Med''. 2023 Jun 12; '''21''' (1):385
Expert-level pediatric brain tumor segmentation in a limited data scenario with stepwise transfer learning. Description: Boyd, Aidan, et al. Expert-level pediatric brain tumor segmentation in a limited data scenario with stepwise transfer learning. ''medRxiv''. 2023 Jun 30;
HLA-DQA1 expression is associated with prognosis and predictable with radiomics in breast cancer. Description: Zhou, JingYu, et al. HLA-DQA1 expression is associated with prognosis and predictable with radiomics in breast cancer. ''Radiat Oncol''. 2023 Jul 11; '''18''' (1):117
Tumor and local lymphoid tissue interaction determines prognosis in high-grade serous ovarian cancer. Description: Lu, Haonan, et al. Tumor and local lymphoid tissue interaction determines prognosis in high-grade serous ovarian cancer. ''Cell Rep Med''. 2023 Jul 18; '''4''' (7):101092
Imaging-Based Versus Pathologic Survival Stratifications of Diffuse Glioma According to the 2021 WHO Classification System. Description: Lee, So Jeong, et al. Imaging-Based Versus Pathologic Survival Stratifications of Diffuse Glioma According to the 2021 WHO Classification System. ''Korean J Radiol''. 2023 Aug; '''24''' (8):772-783
SAMPLER: Empirical distribution representations for rapid analysis of whole slide tissue images. Description: Mukashyaka, Patience, et al. SAMPLER: Empirical distribution representations for rapid analysis of whole slide tissue images. ''bioRxiv''. 2023 Aug 3;
SwarmDeepSurv: swarm intelligence advances deep survival network for prognostic radiomics signatures in four solid cancers. Description: Al-Tashi, Qasem, et al. SwarmDeepSurv: swarm intelligence advances deep survival network for prognostic radiomics signatures in four solid cancers. ''Patterns (N Y)''. 2023 Aug 11; '''4''' (8):100777
CT radiomics prediction of CXCL9 expression and survival in ovarian cancer. Description: Gu, Rui, et al. CT radiomics prediction of CXCL9 expression and survival in ovarian cancer. ''J Ovarian Res''. 2023 Aug 30; '''16''' (1):180
A Large Open Access Dataset of Brain Metastasis 3D Segmentations with Clinical and Imaging Feature Information. Description: Ramakrishnan, Divya, et al. A Large Open Access Dataset of Brain Metastasis 3D Segmentations with Clinical and Imaging Feature Information. ''ArXiv''. 2023 Sep 12;
Prediction of cancer treatment response from histopathology images through imputed transcriptomics. Description: Hoang, Danh-Tai, et al. Prediction of cancer treatment response from histopathology images through imputed transcriptomics. ''Res Sq''. 2023 Sep 15;
A multimodal radiomic machine learning approach to predict the LCK expression and clinical prognosis in high-grade serous ovarian cancer. Description: Zhan, Feng, et al. A multimodal radiomic machine learning approach to predict the LCK expression and clinical prognosis in high-grade serous ovarian cancer. ''Sci Rep''. 2023 Sep 29; '''13''' (1):16397
Radiological Study of Atlas Arch Defects with Meta-Analysis and a Proposed New Classification. Description: Suphamungmee, Worawit, et al. Radiological Study of Atlas Arch Defects with Meta-Analysis and a Proposed New Classification. ''Asian Spine J''. 2023 Oct; '''17''' (5):975-984
ARPC5 acts as a potential prognostic biomarker that is associated with cell proliferation, migration and immune infiltrate in gliomas. Description: Ming, Yue, et al. ARPC5 acts as a potential prognostic biomarker that is associated with cell proliferation, migration and immune infiltrate in gliomas. ''BMC Cancer''. 2023 Oct 3; '''23''' (1):937
Noninvasive radiomic analysis of enhanced CT predicts CTLA4 expression and prognosis in head and neck squamous cell carcinoma. Description: Zhu, Yeping, et al. Noninvasive radiomic analysis of enhanced CT predicts CTLA4 expression and prognosis in head and neck squamous cell carcinoma. ''Sci Rep''. 2023 Oct 5; '''13''' (1):16782
Association of graph-based spatial features with overall survival status of glioblastoma patients. Description: Lee, Joonsang, et al. Association of graph-based spatial features with overall survival status of glioblastoma patients. ''Sci Rep''. 2023 Oct 9; '''13''' (1):17046
CT-based Radiogenomics Framework for COVID-19 Using ACE2 Imaging Representations. Description: Xia, Tian, et al. CT-based Radiogenomics Framework for COVID-19 Using ACE2 Imaging Representations. ''J Digit Imaging''. 2023 Dec; '''36''' (6):2356-2366
Profiling regulatory T lymphocytes within the tumor microenvironment of breast cancer via radiomics. Description: Jiang, Wenying, et al. Profiling regulatory T lymphocytes within the tumor microenvironment of breast cancer via radiomics. ''Cancer Med''. 2023 Dec; '''12''' (24):21861-21872
Deep learning-based segmentation of multisite disease in ovarian cancer. Description: Buddenkotte, Thomas, et al. Deep learning-based segmentation of multisite disease in ovarian cancer. ''Eur Radiol Exp''. 2023 Dec 7; '''7''' (1):77
Lesion detection in women breast's dynamic contrast-enhanced magnetic resonance imaging using deep learning. Description: Saikia, Sudarshan, et al. Lesion detection in women breast's dynamic contrast-enhanced magnetic resonance imaging using deep learning. ''Sci Rep''. 2023 Dec 18; '''13''' (1):22555
A glycolysis-related signature to improve the current treatment and prognostic evaluation for breast cancer. Description: Feng, Sijie, et al. A glycolysis-related signature to improve the current treatment and prognostic evaluation for breast cancer. ''PeerJ''. 2024; '''12''': e17861
A practical guide to FAIR data management in the age of multi-OMICS and AI. Description: Mugahid, Douaa, et al. A practical guide to FAIR data management in the age of multi-OMICS and AI. ''Front Immunol''. 2024; '''15''': 1439434
Comparing the performance of a deep learning-based lung gross tumour volume segmentation algorithm before and after transfer learning in a new hospital. Description: Kulkarni, Chaitanya, et al. Comparing the performance of a deep learning-based lung gross tumour volume segmentation algorithm before and after transfer learning in a new hospital. ''BJR Open''. 2024 Jan; '''6''' (1):tzad008
Comparison of radiomics-based machine-learning classifiers for the pretreatment prediction of pathologic complete response to neoadjuvant therapy in breast cancer. Description: Li, Xue, et al. Comparison of radiomics-based machine-learning classifiers for the pretreatment prediction of pathologic complete response to neoadjuvant therapy in breast cancer. ''PeerJ''. 2024; '''12''': e17683
Enhancing prognostic prediction in hepatocellular carcinoma post-TACE: a machine learning approach integrating radiomics and clinical features. Description: Zhang, Mingqi, et al. Enhancing prognostic prediction in hepatocellular carcinoma post-TACE: a machine learning approach integrating radiomics and clinical features. ''Front Med (Lausanne)''. 2024; '''11''': 1419058
Intensity scaling of conventional brain magnetic resonance images avoiding cerebral reference regions: A systematic review. Description: Wiltgen, Tun, et al. Intensity scaling of conventional brain magnetic resonance images avoiding cerebral reference regions: A systematic review. ''PLoS One''. 2024; '''19''' (3):e0298642
The peritumoral edema index and related mechanisms influence the prognosis of GBM patients. Description: Fang, Zhansheng, et al. The peritumoral edema index and related mechanisms influence the prognosis of GBM patients. ''Front Oncol''. 2024; '''14''': 1417208
Use of fractals in determining the malignancy degree of lung nodules. Description: Amador-Legon, Noel Victor, et al. Use of fractals in determining the malignancy degree of lung nodules. ''Front Med Technol''. 2024; '''6''': 1362688
Focus stacking single-event particle radiography for high spatial resolution images and 3D feature localization. Description: Volz, Lennart, et al. Focus stacking single-event particle radiography for high spatial resolution images and 3D feature localization. ''Phys Med Biol''. 2024 Jan 10; '''69''' (2):
A comparative analysis of CNN-based deep learning architectures for early diagnosis of bone cancer using CT images. Description: Sampath, Kanimozhi, et al. A comparative analysis of CNN-based deep learning architectures for early diagnosis of bone cancer using CT images. ''Sci Rep''. 2024 Jan 25; '''14''' (1):2144
Immune-related lncRNAs signature and radiomics signature predict the prognosis and immune microenvironment of glioblastoma multiforme. Description: Luan, Jixin, et al. Immune-related lncRNAs signature and radiomics signature predict the prognosis and immune microenvironment of glioblastoma multiforme. ''J Transl Med''. 2024 Jan 26; '''22''' (1):107
MRI-derived radiomics assessing tumor-infiltrating macrophages enable prediction of immune-phenotype, immunotherapy response and survival in glioma. Description: Chen, Di, et al. MRI-derived radiomics assessing tumor-infiltrating macrophages enable prediction of immune-phenotype, immunotherapy response and survival in glioma. ''Biomark Res''. 2024 Jan 31; '''12''' (1):14
A clinically relevant computed tomography (CT) radiomics strategy for intracranial rodent brain tumour monitoring. Description: Connor, Kate, et al. A clinically relevant computed tomography (CT) radiomics strategy for intracranial rodent brain tumour monitoring. ''Sci Rep''. 2024 Feb 1; '''14''' (1):2720
Development of End-to-End AI-Based MRI Image Analysis System for Predicting IDH Mutation Status of Patients with Gliomas: Multicentric Validation. Description: Santinha, Joao, et al. Development of End-to-End AI-Based MRI Image Analysis System for Predicting IDH Mutation Status of Patients with Gliomas: Multicentric Validation. ''J Imaging Inform Med''. 2024 Feb; '''37''' (1):31-44
A subregion-based RadioFusionOmics model discriminates between grade 4 astrocytoma and glioblastoma on multisequence MRI. Description: Wei, Ruili, et al. A subregion-based RadioFusionOmics model discriminates between grade 4 astrocytoma and glioblastoma on multisequence MRI. ''J Cancer Res Clin Oncol''. 2024 Feb 2; '''150''' (2):73
Deep representation learning of tissue metabolome and computed tomography annotates NSCLC classification and prognosis. Description: Boubnovski Martell, Marc, et al. Deep representation learning of tissue metabolome and computed tomography annotates NSCLC classification and prognosis. ''NPJ Precis Oncol''. 2024 Feb 3; '''8''' (1):28
A 4D-CBCT correction network based on contrastive learning for dose calculation in lung cancer. Description: Cao, Nannan, et al. A 4D-CBCT correction network based on contrastive learning for dose calculation in lung cancer. ''Radiat Oncol''. 2024 Feb 9; '''19''' (1):20
AI applications in musculoskeletal imaging: a narrative review. Description: Gitto, Salvatore, et al. AI applications in musculoskeletal imaging: a narrative review. ''Eur Radiol Exp''. 2024 Feb 15; '''8''' (1):22
CT radiomics-based model for predicting TMB and immunotherapy response in non-small cell lung cancer. Description: Wang, Jiexiao, et al. CT radiomics-based model for predicting TMB and immunotherapy response in non-small cell lung cancer. ''BMC Med Imaging''. 2024 Feb 15; '''24''' (1):45
Reducing image artifacts in sparse projection CT using conditional generative adversarial networks. Description: Usui, Keisuke, et al. Reducing image artifacts in sparse projection CT using conditional generative adversarial networks. ''Sci Rep''. 2024 Feb 16; '''14''' (1):3917
CT and MRI radiomics of bone and soft-tissue sarcomas: an updated systematic review of reproducibility and validation strategies. Description: Gitto, Salvatore, et al. CT and MRI radiomics of bone and soft-tissue sarcomas: an updated systematic review of reproducibility and validation strategies. ''Insights Imaging''. 2024 Feb 27; '''15''' (1):54
A large open access dataset of brain metastasis 3D segmentations on MRI with clinical and imaging information. Description: Ramakrishnan, Divya, et al. A large open access dataset of brain metastasis 3D segmentations on MRI with clinical and imaging information. ''Sci Data''. 2024 Feb 29; '''11''' (1):254
Conditional generative adversarial network driven radiomic prediction of mutation status based on magnetic resonance imaging of breast cancer. Description: Huang, Zi Huai, et al. Conditional generative adversarial network driven radiomic prediction of mutation status based on magnetic resonance imaging of breast cancer. ''J Transl Med''. 2024 Mar 2; '''22''' (1):226
Synthetic PET from CT improves diagnosis and prognosis for lung cancer: Proof of concept. Description: Salehjahromi, Morteza, et al. Synthetic PET from CT improves diagnosis and prognosis for lung cancer: Proof of concept. ''Cell Rep Med''. 2024 Mar 19; '''5''' (3):101463
Deep learning on tertiary lymphoid structures in hematoxylin-eosin predicts cancer prognosis and immunotherapy response. Description: Chen, Ziqiang, et al. Deep learning on tertiary lymphoid structures in hematoxylin-eosin predicts cancer prognosis and immunotherapy response. ''NPJ Precis Oncol''. 2024 Mar 22; '''8''' (1):73
A radiogenomic multimodal and whole-transcriptome sequencing for preoperative prediction of axillary lymph node metastasis and drug therapeutic response in breast cancer: a retrospective, machine learning and international multicohort study. Description: Lai, Jianguo, et al. A radiogenomic multimodal and whole-transcriptome sequencing for preoperative prediction of axillary lymph node metastasis and drug therapeutic response in breast cancer: a retrospective, machine learning and international multicohort study. ''Int J Surg''. 2024 Apr 1; '''110''' (4):2162-2177
Deep learning-based multi-model prediction for disease-free survival status of patients with clear cell renal cell carcinoma after surgery: a multicenter cohort study. Description: Chen, Siteng, et al. Deep learning-based multi-model prediction for disease-free survival status of patients with clear cell renal cell carcinoma after surgery: a multicenter cohort study. ''Int J Surg''. 2024 May 1; '''110''' (5):2970-2977
Risk assessment model based on nucleotide metabolism-related genes highlights SLC27A2 as a potential therapeutic target in breast cancer. Description: Zhang, Bo, et al. Risk assessment model based on nucleotide metabolism-related genes highlights SLC27A2 as a potential therapeutic target in breast cancer. ''J Cancer Res Clin Oncol''. 2024 May 16; '''150''' (5):258
Automated glioblastoma patient classification using hypoxia levels measured through magnetic resonance images. Description: Shahram, Mohammad Amin, et al. Automated glioblastoma patient classification using hypoxia levels measured through magnetic resonance images. ''BMC Neurosci''. 2024 May 25; '''25''' (1):26
Predicting CD27 expression and clinical prognosis in serous ovarian cancer using CT-based radiomics. Description: Zhang, Chen, et al. Predicting CD27 expression and clinical prognosis in serous ovarian cancer using CT-based radiomics. ''J Ovarian Res''. 2024 Jun 22; '''17''' (1):131
Solving the Pervasive Problem of Protocol Non-Compliance in MRI using an Open-Source tool mrQA. Description: Sinha, Harsh, et al. Solving the Pervasive Problem of Protocol Non-Compliance in MRI using an Open-Source tool mrQA. ''Neuroinformatics''. 2024 Jul; '''22''' (3):297-315
Preoperative prediction of MGMT promoter methylation in glioblastoma based on multiregional and multi-sequence MRI radiomics analysis. Description: Li, Lanqing, et al. Preoperative prediction of MGMT promoter methylation in glioblastoma based on multiregional and multi-sequence MRI radiomics analysis. ''Sci Rep''. 2024 Jul 11; '''14''' (1):16031
Mask region-based convolutional neural network and VGG-16 inspired brain tumor segmentation. Description: Basha, Niha Kamal, et al. Mask region-based convolutional neural network and VGG-16 inspired brain tumor segmentation. ''Sci Rep''. 2024 Jul 30; '''14''' (1):17615
Integrated analysis of spatial transcriptomics and CT phenotypes for unveiling the novel molecular characteristics of recurrent and non-recurrent high-grade serous ovarian cancer. Description: Ju, Hye-Yeon, et al. Integrated analysis of spatial transcriptomics and CT phenotypes for unveiling the novel molecular characteristics of recurrent and non-recurrent high-grade serous ovarian cancer. ''Biomark Res''. 2024 Aug 12; '''12''' (1):80
Tumor contour irregularity on preoperative CT predicts prognosis in renal cell carcinoma: a multi-institutional study. Description: Zhu, Pingyi, et al. Tumor contour irregularity on preoperative CT predicts prognosis in renal cell carcinoma: a multi-institutional study. ''EClinicalMedicine''. 2024 Sep; '''75''': 102775
Radiomics of multi-parametric MRI for the prediction of lung metastasis in soft-tissue sarcoma: a feasibility study. Description: Hu, Yue, et al. Radiomics of multi-parametric MRI for the prediction of lung metastasis in soft-tissue sarcoma: a feasibility study. ''Cancer Imaging''. 2024 Sep 5; '''24''' (1):119
Multicenter radio-multiomic analysis for predicting breast cancer outcome and unravelling imaging-biological connection. Description: You, Chao, et al. Multicenter radio-multiomic analysis for predicting breast cancer outcome and unravelling imaging-biological connection. ''NPJ Precis Oncol''. 2024 Sep 7; '''8''' (1):193
Three-dimensional numerical schemes for the segmentation of the psoas muscle in X-ray computed tomography images. Description: Paolucci, Giulio, et al. Three-dimensional numerical schemes for the segmentation of the psoas muscle in X-ray computed tomography images. ''BMC Med Imaging''. 2024 Sep 19; '''24''' (1):251
Contemporary Update on Clinical and Experimental Prostate Cancer Biomarkers: A Multi-Omics-Focused Approach to Detection and Risk Stratification. Description: Hachem, Sana, et al. Contemporary Update on Clinical and Experimental Prostate Cancer Biomarkers: A Multi-Omics-Focused Approach to Detection and Risk Stratification. ''Biology (Basel)''. 2024 Sep 25; '''13''' (10):
Radiomics Signatures Based on Computed Tomography for Noninvasive Prediction of CXCL10 Expression and Prognosis in Ovarian Cancer. Description: Wang, Xiaohua, et al. Radiomics Signatures Based on Computed Tomography for Noninvasive Prediction of CXCL10 Expression and Prognosis in Ovarian Cancer. ''Cancer Rep (Hoboken)''. 2024 Oct; '''7''' (10):e70030
Transforming Cancer Research through Informatics. Description: Klemm, Juli D, et al. Transforming Cancer Research through Informatics. ''Cancer Discov''. 2024 Oct 4; '''14''' (10):1779-1782
Prediction of homologous recombination deficiency from routine histology with attention-based multiple instance learning in nine different tumor types. Description: Loeffler, Chiara Maria Lavinia, et al. Prediction of homologous recombination deficiency from routine histology with attention-based multiple instance learning in nine different tumor types. ''BMC Biol''. 2024 Oct 8; '''22''' (1):225
Constructing and exploring neuroimaging projects: a survey from clinical practice to scientific research. Description: Chen, Ziyan, et al. Constructing and exploring neuroimaging projects: a survey from clinical practice to scientific research. ''Insights Imaging''. 2024 Nov 15; '''15''' (1):272
Ranking attention multiple instance learning for lymph node metastasis prediction on multicenter cervical cancer MRI. Description: Jin, Shan, et al. Ranking attention multiple instance learning for lymph node metastasis prediction on multicenter cervical cancer MRI. ''J Appl Clin Med Phys''. 2024 Dec; '''25''' (12):e14547
GrandQC: A comprehensive solution to quality control problem in digital pathology. Description: Weng, Zhilong, et al. GrandQC: A comprehensive solution to quality control problem in digital pathology. ''Nat Commun''. 2024 Dec 16; '''15''' (1):10685
Prediction of prognosis, efficacy of lung adenocarcinoma by machine learning model based on immune and metabolic related genes. Description: Xue, Cong, et al. Prediction of prognosis, efficacy of lung adenocarcinoma by machine learning model based on immune and metabolic related genes. ''Discov Oncol''. 2024 Dec 18; '''15''' (1):778
Survival analysis of clear cell renal cell carcinoma based on radiomics and deep learning features from CT images. Description: Lu, Zhennan, et al. Survival analysis of clear cell renal cell carcinoma based on radiomics and deep learning features from CT images. ''Medicine (Baltimore)''. 2024 Dec 20; '''103''' (51):e40723
Prognostic value and immune infiltration of a tumor microenvironment-related PTPN6 in metastatic melanoma. Description: Sun, Rongyao, et al. Prognostic value and immune infiltration of a tumor microenvironment-related PTPN6 in metastatic melanoma. ''Cancer Cell Int''. 2024 Dec 28; '''24''' (1):435
Development and validation of a radiomic prediction model for TACC3 expression and prognosis in non-small cell lung cancer using contrast-enhanced CT imaging. Description: Bai, Weichao, et al. Development and validation of a radiomic prediction model for TACC3 expression and prognosis in non-small cell lung cancer using contrast-enhanced CT imaging. ''Transl Oncol''. 2025 Jan; '''51''': 102211
Exploring adult glioma through MRI: A review of publicly available datasets to guide efficient image analysis. Description: Abbad Andaloussi, Meryem, et al. Exploring adult glioma through MRI: A review of publicly available datasets to guide efficient image analysis. ''Neurooncol Adv''. 2025 Jan-Dec; '''7''' (1):vdae197
Generation of severely scoliotic subject-specific musculoskeletal models. Description: Gould, Samuele Luca, et al. Generation of severely scoliotic subject-specific musculoskeletal models. ''PLoS One''. 2025; '''20''' (12):e0336211
How the First Medical Imaging Cancer Atlas EUCAIM Was Populated: The Experience of a Reference Hospital. Description: Penades Blasco, Ana, et al. How the First Medical Imaging Cancer Atlas EUCAIM Was Populated: The Experience of a Reference Hospital. ''Open Res Eur''. 2025; '''5''': 310
Integration of histopathological image features and multi-dimensional omics data in predicting molecular features and survival in glioblastoma. Description: Huang, Yeqian, et al. Integration of histopathological image features and multi-dimensional omics data in predicting molecular features and survival in glioblastoma. ''Front Med (Lausanne)''. 2025; '''12''': 1510793
Integration of histopathological images and immunological analysis to predict M2 macrophage infiltration and prognosis in patients with serous ovarian cancer. Description: Zhao, Ling, et al. Integration of histopathological images and immunological analysis to predict M2 macrophage infiltration and prognosis in patients with serous ovarian cancer. ''Front Immunol''. 2025; '''16''': 1505509
Multimodal MRI radiomics based on habitat subregions of the tumor microenvironment for predicting risk stratification in glioblastoma. Description: Wang, Han. Multimodal MRI radiomics based on habitat subregions of the tumor microenvironment for predicting risk stratification in glioblastoma. ''PLoS One''. 2025; '''20''' (6):e0326361
Multi-platform integration of histopathological images and omics data predicts molecular features and prognosis of hepatocellular carcinoma. Description: Chen, Linyan, et al. Multi-platform integration of histopathological images and omics data predicts molecular features and prognosis of hepatocellular carcinoma. ''Front Oncol''. 2025; '''15''': 1591165
Multi-scale error-driven dense residual network for image super-resolution reconstruction. Description: Li, Xueri, et al. Multi-scale error-driven dense residual network for image super-resolution reconstruction. ''PLoS One''. 2025; '''20''' (9):e0330615
Predicting podoplanin expression and prognostic significance in high-grade glioma based on TCGA TCIA radiomics. Description: Long, Shengrong, et al. Predicting podoplanin expression and prognostic significance in high-grade glioma based on TCGA TCIA radiomics. ''PLoS One''. 2025; '''20''' (6):e0325964
The dual role of CXCL9/SPP1 polarized tumor-associated macrophages in modulating anti-tumor immunity in hepatocellular carcinoma. Description: Gu, Yu, et al. The dual role of CXCL9/SPP1 polarized tumor-associated macrophages in modulating anti-tumor immunity in hepatocellular carcinoma. ''Front Immunol''. 2025; '''16''': 1528103
Increased SOAT2 expression in aged regulatory T cells is associated with altered cholesterol metabolism and reduced anti-tumor immunity. Description: Zhang, Mingjiong, et al. Increased SOAT2 expression in aged regulatory T cells is associated with altered cholesterol metabolism and reduced anti-tumor immunity. ''Nat Commun''. 2025 Jan 13; '''16''' (1):630
AI-assisted Segmentation Tool for Brain Tumor MR Image Analysis. Description: Lee, Myungeun, et al. AI-assisted Segmentation Tool for Brain Tumor MR Image Analysis. ''J Imaging Inform Med''. 2025 Feb; '''38''' (1):74-83
MAZ-mediated tumor progression and immune evasion in hormone receptor-positive breast cancer: Targeting tumor microenvironment and PCLAF+ subtype-specific therapy. Description: Ni, Gaofeng, et al. MAZ-mediated tumor progression and immune evasion in hormone receptor-positive breast cancer: Targeting tumor microenvironment and PCLAF+ subtype-specific therapy. ''Transl Oncol''. 2025 Feb; '''52''': 102280
Simplifying Radiomics Workflow for Predicting Grade of Glioma: An Approach for Rapid and Reproducible Radiomics. Description: Soleymani, Yunus, et al. Simplifying Radiomics Workflow for Predicting Grade of Glioma: An Approach for Rapid and Reproducible Radiomics. ''J Biomed Phys Eng''. 2025 Feb; '''15''' (1):27-36
Enhancing deep learning methods for brain metastasis detection through cross-technique annotations on SPACE MRI. Description: Wald, Tassilo, et al. Enhancing deep learning methods for brain metastasis detection through cross-technique annotations on SPACE MRI. ''Eur Radiol Exp''. 2025 Feb 6; '''9''' (1):15
Artificial intelligence links CT images to pathologic features and survival outcomes of renal masses. Description: Xiong, Ying, et al. Artificial intelligence links CT images to pathologic features and survival outcomes of renal masses. ''Nat Commun''. 2025 Feb 7; '''16''' (1):1425
Molecular subtyping combined with multiomics analysis to study correlation between TACE refractoriness and tumor stemness in hepatocellular carcinoma. Description: He, Qifan, et al. Molecular subtyping combined with multiomics analysis to study correlation between TACE refractoriness and tumor stemness in hepatocellular carcinoma. ''Discov Oncol''. 2025 Feb 17; '''16''' (1):197
Tumour surface regularity predicts survival and benefit from gross total resection in IDH-wildtype glioblastoma patients. Description: Lin, Peng, et al. Tumour surface regularity predicts survival and benefit from gross total resection in IDH-wildtype glioblastoma patients. ''Insights Imaging''. 2025 Feb 17; '''16''' (1):42
MRI radiomics based on machine learning in high-grade gliomas as a promising tool for prediction of CD44 expression and overall survival. Description: Yu, Mingjun, et al. MRI radiomics based on machine learning in high-grade gliomas as a promising tool for prediction of CD44 expression and overall survival. ''Sci Rep''. 2025 Mar 3; '''15''' (1):7433
Interpretable multimodal transformer for prediction of molecular subtypes and grades in adult-type diffuse gliomas. Description: Byeon, Yunsu, et al. Interpretable multimodal transformer for prediction of molecular subtypes and grades in adult-type diffuse gliomas. ''NPJ Digit Med''. 2025 Mar 5; '''8''' (1):140
Prediction and analysis of tumor infiltrating lymphocytes across 28 cancers by TILScout using deep learning. Description: Zhang, Huibo, et al. Prediction and analysis of tumor infiltrating lymphocytes across 28 cancers by TILScout using deep learning. ''NPJ Precis Oncol''. 2025 Mar 19; '''9''' (1):76
Synthetic bone marrow images augment real samples in developing acute myeloid leukemia microscopy classification models. Description: Eckardt, Jan-Niklas, et al. Synthetic bone marrow images augment real samples in developing acute myeloid leukemia microscopy classification models. ''NPJ Digit Med''. 2025 Mar 22; '''8''' (1):173
MRI transformer deep learning and radiomics for predicting IDH wild type TERT promoter mutant gliomas. Description: Niu, Wenju, et al. MRI transformer deep learning and radiomics for predicting IDH wild type TERT promoter mutant gliomas. ''NPJ Precis Oncol''. 2025 Mar 27; '''9''' (1):89
Construction of enhanced MRI-based radiomics models using machine learning algorithms for non-invasive prediction of IL7R expression in high-grade gliomas and its prognostic value in clinical practice. Description: Zhou, Jie. Construction of enhanced MRI-based radiomics models using machine learning algorithms for non-invasive prediction of IL7R expression in high-grade gliomas and its prognostic value in clinical practice. ''J Transl Med''. 2025 Mar 31; '''23''' (1):383
Artificial intelligence predicts multiclass molecular signatures and subtypes directly from breast cancer histology: a multicenter retrospective study. Description: Zhang, Xiangyang, et al. Artificial intelligence predicts multiclass molecular signatures and subtypes directly from breast cancer histology: a multicenter retrospective study. ''Int J Surg''. 2025 Apr 1; '''111''' (4):3109-3114
CCL26 as a prognostic biomarker in hepatocellular carcinoma: integrating bioinformatics analysis, clinical validation, and radiomics score. Description: Yan, Junjun, et al. CCL26 as a prognostic biomarker in hepatocellular carcinoma: integrating bioinformatics analysis, clinical validation, and radiomics score. ''Discov Oncol''. 2025 Apr 9; '''16''' (1):502
Development of a radiomic model to predict CEACAM1 expression and prognosis in ovarian cancer. Description: Zhang, Xiaoxue, et al. Development of a radiomic model to predict CEACAM1 expression and prognosis in ovarian cancer. ''Sci Rep''. 2025 Apr 30; '''15''' (1):15259
Machine learning and single-cell analysis uncover distinctive characteristics of CD300LG within the TNBC immune microenvironment: experimental validation. Description: Zhu, Baoxi, et al. Machine learning and single-cell analysis uncover distinctive characteristics of CD300LG within the TNBC immune microenvironment: experimental validation. ''Clin Exp Med''. 2025 May 17; '''25''' (1):167
Multimodal fusion model for prognostic prediction and radiotherapy response assessment in head and neck squamous cell carcinoma. Description: Tian, Ruxian, et al. Multimodal fusion model for prognostic prediction and radiotherapy response assessment in head and neck squamous cell carcinoma. ''NPJ Digit Med''. 2025 May 23; '''8''' (1):302
Enhanced magnetic resonance imaging-based radiomics predicts CD40LG expression and survival in high-grade gliomas: a retrospective study. Description: He, Jie, et al. Enhanced magnetic resonance imaging-based radiomics predicts CD40LG expression and survival in high-grade gliomas: a retrospective study. ''Discov Oncol''. 2025 May 30; '''16''' (1):962
MRI features and prognostic evaluation in patients with subventricular zone-contacting IDH-wild-type glioblastoma. Description: Pan, Shijiao, et al. MRI features and prognostic evaluation in patients with subventricular zone-contacting IDH-wild-type glioblastoma. ''Radiol Oncol''. 2025 Jun 1; '''59''' (2):1-8
Uncertainty Estimation for Dual View X-ray Mammographic Image Registration Using Deep Ensembles. Description: Walton, William C, et al. Uncertainty Estimation for Dual View X-ray Mammographic Image Registration Using Deep Ensembles. ''J Imaging Inform Med''. 2025 Jun; '''38''' (3):1829-1845
Integration of MRI radiomics and germline genetics to predict the IDH mutation status of gliomas. Description: Nakase, Taishi, et al. Integration of MRI radiomics and germline genetics to predict the IDH mutation status of gliomas. ''NPJ Precis Oncol''. 2025 Jun 16; '''9''' (1):187
Machine learning-based MRI radiomics predict IL18 expression and overall survival of low-grade glioma patients. Description: Zhang, Zhe, et al. Machine learning-based MRI radiomics predict IL18 expression and overall survival of low-grade glioma patients. ''NPJ Precis Oncol''. 2025 Jun 19; '''9''' (1):196
Computational image and molecular analysis reveal unique prognostic features of immune architecture in African Versus European American women with endometrial cancer. Description: Azarianpour, Sepideh, et al. Computational image and molecular analysis reveal unique prognostic features of immune architecture in African Versus European American women with endometrial cancer. ''NPJ Precis Oncol''. 2025 Jun 23; '''9''' (1):203
Development and validation of a fusion model based on multi-phase contrast CT radiomics combined with clinical features for predicting Ki-67 expression in gastric cancer. Description: Song, Tianjun, et al. Development and validation of a fusion model based on multi-phase contrast CT radiomics combined with clinical features for predicting Ki-67 expression in gastric cancer. ''Biomed Rep''. 2025 Jul; '''23''' (1):118
Machine learning model for predicting tertiary lymphoid structures and treatment response in triple-negative breast cancer. Description: Lin, Yidan, et al. Machine learning model for predicting tertiary lymphoid structures and treatment response in triple-negative breast cancer. ''NPJ Precis Oncol''. 2025 Jul 1; '''9''' (1):216
Stochastic differential equation modeling approach for grading astrocytomas on brain MRI images. Description: Raisi-Nafchi, Mahsa, et al. Stochastic differential equation modeling approach for grading astrocytomas on brain MRI images. ''Sci Rep''. 2025 Jul 2; '''15''' (1):22835
Attention-based multimodal deep learning for interpretable and generalizable prediction of pathological complete response in breast cancer. Description: Nishizawa, Taishi, et al. Attention-based multimodal deep learning for interpretable and generalizable prediction of pathological complete response in breast cancer. ''J Transl Med''. 2025 Jul 10; '''23''' (1):774
Predicting exploratory thoracotomy in non-small cell lung cancer: a computed tomography based nomogram approach. Description: Dai, Fuqiang, et al. Predicting exploratory thoracotomy in non-small cell lung cancer: a computed tomography based nomogram approach. ''BMC Cancer''. 2025 Jul 10; '''25''' (1):1161
Bi-Regional Machine Learning Radiomics Based on CT Noninvasively Predicts LOX Expression Level and Overall Survival in Hepatocellular Carcinoma. Description: Gao, Kexin, et al. Bi-Regional Machine Learning Radiomics Based on CT Noninvasively Predicts LOX Expression Level and Overall Survival in Hepatocellular Carcinoma. ''Cancer Med''. 2025 Aug; '''14''' (15):e71154
Multimodal data curation via interoperability: use cases with the Medical Imaging and Data Resource Center. Description: Chen, Weijie, et al. Multimodal data curation via interoperability: use cases with the Medical Imaging and Data Resource Center. ''Sci Data''. 2025 Aug 1; '''12''' (1):1340
Innovative machine learning approach for liver fibrosis and disease severity evaluation in MAFLD patients using MRI fat content analysis. Description: Hou, Mengting, et al. Innovative machine learning approach for liver fibrosis and disease severity evaluation in MAFLD patients using MRI fat content analysis. ''Clin Exp Med''. 2025 Aug 5; '''25''' (1):275
A stacking ensemble framework integrating radiomics and deep learning for prognostic prediction in head and neck cancer. Description: Wang, Bingzhen, et al. A stacking ensemble framework integrating radiomics and deep learning for prognostic prediction in head and neck cancer. ''Radiat Oncol''. 2025 Aug 13; '''20''' (1):127
Research Priorities for Translating Endophenotyping of Adult Obstructive Sleep Apnea to the Clinic: An Official American Thoracic Society Research Statement. Description: Tolbert, Thomas M, et al. Research Priorities for Translating Endophenotyping of Adult Obstructive Sleep Apnea to the Clinic: An Official American Thoracic Society Research Statement. ''Am J Respir Crit Care Med''. 2025 Sep; '''211''' (9):1562-1583
Uncovering novel functions of NUF2 in glioblastoma and MRI-based expression prediction. Description: Zhong, Rong-de, et al. Uncovering novel functions of NUF2 in glioblastoma and MRI-based expression prediction. ''Sci Rep''. 2025 Sep 1; '''15''' (1):32120
A pipeline to morph finite element models of the lumbar spine for generation of customised spinal cages. Description: Yu, Yihang, et al. A pipeline to morph finite element models of the lumbar spine for generation of customised spinal cages. ''J Orthop Surg Res''. 2025 Sep 29; '''20''' (1):864
Survival risk stratification of 2021 WHO glioblastoma by MRI radiomics and biological exploration. Description: Li, Yangyang, et al. Survival risk stratification of 2021 WHO glioblastoma by MRI radiomics and biological exploration. ''BMC Cancer''. 2025 Oct 3; '''25''' (1):1505
Real-World Benchmarking and Validation of Foundation Model Transformers for Endometrial Cancer Subtyping from Histopathology. Description: Wagner, Vincent M, et al. Real-World Benchmarking and Validation of Foundation Model Transformers for Endometrial Cancer Subtyping from Histopathology. ''medRxiv''. 2025 Oct 13;
RadGLO: an interactive platform for radiomic feature analysis and prognostic modeling in glioma. Description: Kundal, Kavita, et al. RadGLO: an interactive platform for radiomic feature analysis and prognostic modeling in glioma. ''NPJ Precis Oncol''. 2025 Oct 14; '''9''' (1):323
An integrated MRI-based diagnostic framework for glioma with incomplete imaging sequences and imperfect annotations. Description: Song, Pengfei, et al. An integrated MRI-based diagnostic framework for glioma with incomplete imaging sequences and imperfect annotations. ''NPJ Precis Oncol''. 2025 Oct 23; '''9''' (1):328
CT radiomic stratification signature to optimize clinical decisions for ovarian cancer patients receiving neoadjuvant chemotherapy and the underlying biological basis: a multicenter retrospective study. Description: Zhang, Shimin, et al. CT radiomic stratification signature to optimize clinical decisions for ovarian cancer patients receiving neoadjuvant chemotherapy and the underlying biological basis: a multicenter retrospective study. ''J Transl Med''. 2025 Oct 28; '''23''' (1):1184
Radiomic imaging models for predicting breast cancer prognosis based on Interleukin-18 (IL18). Description: Zhou, Qian, et al. Radiomic imaging models for predicting breast cancer prognosis based on Interleukin-18 (IL18). ''BMC Med Imaging''. 2025 Nov 12; '''25''' (1):460
STPath: a generative foundation model for integrating spatial transcriptomics and whole-slide images. Description: Huang, Tinglin, et al. STPath: a generative foundation model for integrating spatial transcriptomics and whole-slide images. ''NPJ Digit Med''. 2025 Nov 14; '''8''' (1):659