{"id":"W2983431646","doi":"10.3389/fncom.2019.00072","title":"Prediction and Classification of Alzheimer’s Disease Based on Combined Features From Apolipoprotein-E Genotype, Cerebrospinal Fluid, MR, and FDG-PET Imaging Biomarkers","year":2019,"lang":"en","type":"article","venue":"Frontiers in Computational Neuroscience","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":152,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute on Aging; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Meso Scale Diagnostics; National Research Foundation of Korea; National Research Foundation; Northern California Institute for Research and Education; F. Hoffmann-La Roche; University of Southern California; Pfizer; BioClinica; Biogen; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; Ministry of Science and ICT, South Korea; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Alzheimer's Association","keywords":"Biomarker; Apolipoprotein E; Dementia; Medicine; Disease; Neuroimaging; Cerebrospinal fluid; Internal medicine; Imaging biomarker; Oncology; Artificial intelligence; Magnetic resonance imaging; Radiology; Computer science; 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":[0.00112975,0.0008492444,0.001064832,0.002105493,0.0001976635,0.0007506708,0.0004190904,0.0005683852,0.000359041],"category_scores_gemma":[0.001548671,0.0001289153,0.0006626355,0.0005534653,0.0001892702,0.0003933584,0.0004787915,0.000458471,0.0001856607],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002771454,"about_ca_system_score_gemma":0.0004799734,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00420235,"about_ca_topic_score_gemma":0.003941977,"domain_scores_codex":[0.9996313,0.00008830534,0.00005588886,0.00009657234,0.00006540067,0.00006249342],"domain_scores_gemma":[0.9992849,0.0002265545,0.0001404177,0.00004411799,0.0001755101,0.0001285434],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002082866,0.000940097,0.7799316,0.0001243074,0.0005356828,0.0005712621,0.0001062588,0.02701068,0.008872896,0.0002736158,0.003118442,0.1764323],"study_design_scores_gemma":[0.0001131361,0.000546146,0.3205969,0.00005643239,0.0002839427,0.0003624843,0.0001936718,0.6731015,0.002602651,0.001257239,0.0008324116,0.00005352325],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9869924,0.001091138,0.010296,0.0001886687,0.00005185551,0.00004409095,0.0007191935,0.0001080026,0.0005086886],"genre_scores_gemma":[0.9926727,0.0002480923,0.005565376,0.0000397784,0.00006089465,0.00002851088,0.00114398,0.000003521038,0.0002369816],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00420235,"threshold_uncertainty_score":0.008355737,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01662354629166961,"score_gpt":0.2745878401972464,"score_spread":0.2579642939055768,"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."}}