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Supervised machine learning for diagnostic classification from large-scale neuroimaging datasets |
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| Authors: | Lanka Pradyumna Rangaprakash D Dretsch Michael N Katz Jeffrey S Denney Thomas S Deshpande Gopikrishna |
| Institution: | 1.AU MRI Research Center, Department of Electrical and Computer Engineering, Auburn University, 560 Devall Dr., Suite 266D, Auburn, AL, 36849, USA ;2.Department of Psychological Sciences, University of California Merced, Merced, CA, USA ;3.Departments of Radiology and Biomedical Engineering, Northwestern University, Chicago, IL, USA ;4.U.S. Army Aeromedical Research Laboratory, Fort Rucker, AL, USA ;5.US Army Medical Research Directorate-West, Walter Reed Army Institute for Research, Joint Base Lewis-McCord, WA, USA ;6.Department of Psychology, Auburn University, Auburn, AL, USA ;7.Alabama Advanced Imaging Consortium, Birmingham, AL, USA ;8.Center for Neuroscience, Auburn University, Auburn, AL, USA ;9.Center for Health Ecology and Equity Research, Auburn University, Auburn, AL, USA ;10.Department of Psychiatry, National Institute of Mental and Neurosciences, Bangalore, India ; |
| Abstract: | Brain Imaging and Behavior - There are growing concerns about the generalizability of machine learning classifiers in neuroimaging. In order to evaluate this aspect across relatively large... |
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