{"id":"W3125069671","doi":"10.1038/s41598-021-82098-3","title":"A multilayer multimodal detection and prediction model based on explainable artificial intelligence for Alzheimer’s disease","year":2021,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":344,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; Genentech; National Institutes of Health; IXICO; H. Lundbeck A/S; Servier; Eisai; Meso Scale Diagnostics; National Research Foundation of Korea; National Research Foundation; Ministerio de Ciencia, Innovación y Universidades; Northern California Institute for Research and Education; Ministry of Science and ICT, South Korea; Pfizer; Biogen; BioClinica; F. Hoffmann-La Roche; University of Southern California; European Regional Development Fund; Mansoura University; Eli Lilly and Company; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Bristol-Myers Squibb; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Neuroimaging; Artificial intelligence; Random forest; Computer science; Classifier (UML); Dementia; Machine learning; Binary classification; Disease; Cognitive impairment; Modalities; Cognition; Set (abstract data type); Psychology; Medicine; Psychiatry; Pathology; Support vector machine","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04523720198627321,"score_gpt":0.3117149733472688,"score_spread":0.2664777713609956,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}