{"id":"W4285172834","doi":"10.1109/access.2022.3174601","title":"Deviation From Model of Normal Aging in Alzheimer’s Disease: Application of Deep Learning to Structural MRI Data and Cognitive Tests","year":2022,"lang":"en","type":"article","venue":"IEEE Access","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; United Arab Emirates University; Eisai; Northern California Institute for Research and Education; Pfizer; Biogen; BioClinica; F. Hoffmann-La Roche; University of Southern California; Eli Lilly and Company; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Bristol-Myers Squibb; National Institute on Aging; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Dementia; Neurocognitive; Cognition; Alzheimer's disease; Audiology; Disease; Medicine; Neuropsychology; Psychology; Physical medicine and rehabilitation; Neuroscience; Internal medicine","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004098341,0.0009924178,0.0006804606,0.0009111706,0.0002896249,0.0009006672,0.0009226407,0.0009685335,0.0006759736],"category_scores_gemma":[0.007570446,0.0003204638,0.0009538725,0.0003663702,0.0005408644,0.000596654,0.0007028158,0.001448838,0.0002072772],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001508747,"about_ca_system_score_gemma":0.001045498,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01969246,"about_ca_topic_score_gemma":0.009489948,"domain_scores_codex":[0.9991646,0.0003757607,0.00005129498,0.0002084198,0.00009753014,0.0001023143],"domain_scores_gemma":[0.9968996,0.002145695,0.000311378,0.0001420297,0.0003854947,0.0001158638],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0003283324,0.0001472334,0.02530458,0.00004522244,0.0002110445,0.0001074583,0.00005981979,0.9410492,0.0009744391,0.00125853,0.0007717565,0.02974243],"study_design_scores_gemma":[0.000003660351,0.00002626608,0.001580144,0.0000039641,0.000007767898,0.00001355176,0.000003109847,0.9974281,0.0001154153,0.0007775132,0.00003700906,0.000003419377],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7112162,0.001079134,0.2836334,0.001283341,0.00009411269,0.0001020857,0.0006457531,0.0006181978,0.001327852],"genre_scores_gemma":[0.9879835,0.000137265,0.01021708,0.0001032399,0.0000239016,0.00006059359,0.0005395731,0.00002119134,0.0009136868],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01969246,"threshold_uncertainty_score":0.03915566,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05052402105059813,"score_gpt":0.3861856618986642,"score_spread":0.3356616408480661,"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."}}