Model-Based and Model-Free Techniques for Amyotrophic Lateral Sclerosis Diagnostic Prediction and Patient Clustering
Year: 2018
Type: article
Source: Neuroinformatics
Institution: University of Michigan
Language: English
Subfield: Clinical Neurology
Field: Medicine
Domain: Health Sciences
Open Access status: green
Funders: National Science Foundation, National Institutes of Health, National Institute on Aging, National Institute of Nursing Research, National Institute of Diabetes and Digestive and Kidney Diseases, National Institute of Neurological Disorders and Stroke, National Institute of Environmental Health Sciences, National Institute of Biomedical Imaging and Bioengineering, National Center for Advancing Translational Sciences
Awards: Michigan Alzheimer's Disease Core Center, Big Data for Discovery Science, Cholinergic mechanisms of attentional-motor integration and gait dysfunction in Parkinson Disease, Center for Complexity and Self-management of Chronic Disease (CSCD), Impact of Geospatial Factors and Environmental Pollutants on Amyotrophic Lateral Sclerosis in the State of Michigan, Michigan Institute for Clinical and Health Research (MICHR), NCS-FO: Connectome mapping algorithms with application to community services for big data neuroscience, G9000288353, Michigan Nutrition Obesity Research Center
OpenAlex ID: W2900689183