{"id":"W4401824770","doi":"10.1016/j.heliyon.2024.e36728","title":"Prediction of future dementia among patients with mild cognitive impairment (MCI) by integrating multimodal clinical data","year":2024,"lang":"en","type":"article","venue":"Heliyon","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":5,"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; Eisai; National Institute of Neurological Disorders and Stroke; Northern California Institute for Research and Education; Pfizer; Novartis Pharmaceuticals Corporation; National Human Genome Research Institute; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; National Institute on Aging; Alzheimer's Association","keywords":"Dementia; Cognitive impairment; Cognition; Psychology; Medicine; Gerontology; Clinical psychology; Psychiatry; Internal medicine; Disease","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":[0.002426219,0.001040984,0.0006685465,0.001468837,0.0002839424,0.0007545772,0.0004088735,0.0005937175,0.0003755725],"category_scores_gemma":[0.004989049,0.000178159,0.0007980471,0.0005451584,0.0001650022,0.00071211,0.0007129476,0.001040438,0.0001893453],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003783379,"about_ca_system_score_gemma":0.0005093582,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007232469,"about_ca_topic_score_gemma":0.01014245,"domain_scores_codex":[0.9995536,0.0001800028,0.00003644599,0.0001237713,0.00005713399,0.00004908639],"domain_scores_gemma":[0.9984388,0.0008156315,0.0002500381,0.00009493355,0.0002757787,0.000124761],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008467072,0.0006943022,0.6912325,0.0001076657,0.0006057197,0.0002986228,0.0002212344,0.09872201,0.00274417,0.0003345385,0.002344376,0.2018482],"study_design_scores_gemma":[0.0000290275,0.0005696362,0.1485421,0.00005734233,0.0002791905,0.0003086873,0.0001764413,0.845497,0.002011829,0.001820588,0.0006600954,0.00004819136],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9643971,0.001217817,0.03164098,0.0005391845,0.00004982322,0.0000711217,0.0009468299,0.0002811159,0.0008559992],"genre_scores_gemma":[0.9885764,0.0002430155,0.009890307,0.00008488988,0.00003519788,0.00002889528,0.0009266462,0.000007477748,0.0002072043],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007232469,"threshold_uncertainty_score":0.01438069,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03303215511529351,"score_gpt":0.3440781759963713,"score_spread":0.3110460208810778,"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."}}