{"id":"W2783976217","doi":"10.3389/fnhum.2017.00643","title":"A Novel Early Diagnosis System for Mild Cognitive Impairment Based on Local Region Analysis: A Pilot Study","year":2018,"lang":"en","type":"article","venue":"Frontiers in Human Neuroscience","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":13,"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; Northern California Institute for Research and Education; BioClinica; F. Hoffmann-La Roche; University of Southern California; Biogen; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Pfizer; Eli Lilly and Company; Bristol-Myers Squibb; National Institute on Aging; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Cognitive impairment; Dementia; Artificial intelligence; Support vector machine; Neuroimaging; Pattern recognition (psychology); Computer science; Medicine; Disease; Psychology; Pathology; Neuroscience","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":[0.00129653,0.0005028031,0.0005862891,0.0007527336,0.000295917,0.0005159675,0.0006433539,0.0005583126,0.003100915],"category_scores_gemma":[0.002196518,0.0001531763,0.0004477173,0.0003476338,0.0001815654,0.0006347189,0.0004539404,0.0002417764,0.000837441],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002589601,"about_ca_system_score_gemma":0.0004251263,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003598475,"about_ca_topic_score_gemma":0.002222785,"domain_scores_codex":[0.9996645,0.00009883552,0.00003019074,0.0001075765,0.00006104308,0.00003784324],"domain_scores_gemma":[0.9990498,0.0002431411,0.0000283499,0.0001350314,0.0004489419,0.00009459732],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.005966417,0.002567648,0.06142072,0.0006794663,0.0004344653,0.002191281,0.0007760575,0.01021342,0.1792981,0.000924179,0.005849682,0.7296786],"study_design_scores_gemma":[0.002008532,0.01660415,0.1561858,0.00009659548,0.001318299,0.006342876,0.001133033,0.6602184,0.1425813,0.001352117,0.01189341,0.0002654113],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8891875,0.0006280272,0.1038778,0.0001477868,0.000116993,0.001036825,0.0008024685,0.002803858,0.001398769],"genre_scores_gemma":[0.8807496,0.0002616135,0.1157058,0.00008478182,0.00007233249,0.000509371,0.001021761,0.00007065845,0.001524109],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003598475,"threshold_uncertainty_score":0.01037353,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05805418880502114,"score_gpt":0.3397025613651228,"score_spread":0.2816483725601017,"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."}}