{"id":"W1541966155","doi":"10.1155/2015/961314","title":"Improved Diagnostic Multimodal Biomarkers for Alzheimer’s Disease and Mild Cognitive Impairment","year":2015,"lang":"en","type":"article","venue":"BioMed Research International","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":27,"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; University of California, San Diego; National Institutes of Health; Genentech; IXICO; Servier; Instituto Tecnológico y de Estudios Superiores de Monterrey; Eisai; Northern California Institute for Research and Education; DoD Alzheimer's Disease Neuroimaging Initiative; Pfizer; Biogen; BioClinica; F. Hoffmann-La Roche; Consejo Nacional de Ciencia y Tecnología; Synarc; University of Southern California; Medpace; Novartis Pharmaceuticals Corporation; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Feature selection; Neuroimaging; Disease; Cognitive impairment; Logistic regression; Medicine; Alzheimer's disease; Biomarker; Classifier (UML); Cognition; Artificial intelligence; Pathology; Computer science; Internal medicine; Psychiatry; Biology","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":[0.00472311,0.0008509965,0.0009944873,0.002544679,0.000278289,0.001029353,0.0004481573,0.0005420865,0.001498393],"category_scores_gemma":[0.01002574,0.0001707707,0.0009875303,0.001286576,0.0002278451,0.0007783307,0.0007662873,0.0006028618,0.0003694885],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004631487,"about_ca_system_score_gemma":0.0006422978,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002026218,"about_ca_topic_score_gemma":0.003214703,"domain_scores_codex":[0.998738,0.0006118719,0.0001281542,0.0001946286,0.0002214662,0.000105928],"domain_scores_gemma":[0.9977254,0.001144861,0.0004524928,0.0002054988,0.0003919303,0.00007992656],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002345578,0.0008785179,0.4446262,0.0003312004,0.0009616309,0.0004096607,0.0002110672,0.0195899,0.03234464,0.001305207,0.003309679,0.4936866],"study_design_scores_gemma":[0.000256541,0.002190967,0.7189758,0.0002181723,0.001290776,0.001629465,0.0002273341,0.2385806,0.02341015,0.008510192,0.004559757,0.00015027],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9364274,0.003231033,0.05506825,0.0004766116,0.00004552279,0.0002662489,0.002367607,0.0003644737,0.001752881],"genre_scores_gemma":[0.9516785,0.0003092602,0.04563617,0.00007399897,0.00004006163,0.0001127461,0.001671465,0.00001205496,0.0004658612],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00472311,"threshold_uncertainty_score":0.02497852,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.11137200569748,"score_gpt":0.4343407199845616,"score_spread":0.3229687142870816,"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."}}