http://www.nitrc.org/forum/forum.php?forum_id=9018 <table border="0" width="100%"><tr><td align="left"/><td align="right"><a href="https://www.ncbi.nlm.nih.gov/sites/entrez?db=pubmed&amp;cmd=Link&amp;LinkName=pubmed_pubmed&amp;from_uid=30245275">Related Articles</a></td></tr></table> <p><b>Predicting conversion from MCI to AD by integrating rs-fMRI and structural MRI.</b></p> <p>Comput Biol Med. 2018 Sep 15;102:30-39</p> <p>Authors: Hojjati SH, Ebrahimzadeh A, Khazaee A, Babajani-Feremi A, Alzheimer's Disease Neuroimaging Initiative</p> <p>Abstract<br/> Structural MRI (sMRI) and resting-state functional MRI (rs-fMRI) have provided promising results in the diagnosis of Alzheimer's disease (AD), though the utility of integrating sMRI with rs-fMRI has not been explored thoroughly. We investigated the performances of rs-fMRI and sMRI in single modality and multi-modality approaches for classifying patients with mild cognitive impairment (MCI) who progress to probable AD-MCI converter (MCI-C) from those with MCI who do not progress to probable AD-MCI non-converter (MCI-NC). The cortical and subcortical measurements, e.g. cortical thickness, extracted from sMRI and graph measures extracted from rs-fMRI functional connectivity were used as features in our algorithm. We trained and tested a support vector machine to classify MCI-C from MCI-NC using rs-fMRI and sMRI features. Our algorithm for classifying MCI-C and MCI-NC utilized a small number of optimal features and achieved accuracies of 89% for sMRI, 93% for rs-fMRI, and 97% for the combination of sMRI with rs-fMRI. To our knowledge, this is the first study that investigated integration of rs-fMRI and sMRI for identification of the early stage of AD. Our findings shed light on integration of sMRI with rs-fMRI for identification of the early stages of AD.<br/> </p><p>PMID: 30245275 [PubMed - as supplied by publisher]</p> en-us Copyright 2000-2026 NITRC OSI Mon, 25 May 2026 16:53:09 GMT http://blogs.law.harvard.edu/tech/rss NITRC RSS generator