{"id":"W2909341957","doi":"10.3389/fnins.2018.01045","title":"Dual-Model Radiomic Biomarkers Predict Development of Mild Cognitive Impairment Progression to Alzheimer’s Disease","year":2019,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":68,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute on Aging; National Key Research and Development Program of China; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; University of California, San Diego; National Institutes of Health; H. Lundbeck A/S; Servier; National Natural Science Foundation of China; Eisai; Genentech; IXICO; Fudan University; 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; Foundation for the National Institutes of Health; Science and Technology Commission of Shanghai Municipality; Novartis Pharmaceuticals Corporation; Bristol-Myers Squibb; Alzheimer's Association","keywords":"Magnetic resonance imaging; Positron emission tomography; Neuroimaging; Alzheimer's Disease Neuroimaging Initiative; Medicine; Multivariate statistics; Proportional hazards model; Cognitive impairment; Nuclear medicine; Disease; Internal medicine; Radiology; Computer science; Machine learning","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":[0.003025129,0.0008359386,0.0008128874,0.001517941,0.0002194069,0.001161875,0.0009268002,0.0006877223,0.0007285307],"category_scores_gemma":[0.004439536,0.0003077753,0.001296946,0.0005502132,0.0002957659,0.0006899277,0.0007725879,0.0007497232,0.0002969803],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004286189,"about_ca_system_score_gemma":0.000616126,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002245611,"about_ca_topic_score_gemma":0.002335926,"domain_scores_codex":[0.999348,0.0002224658,0.0000368151,0.0002032296,0.0001016928,0.00008776206],"domain_scores_gemma":[0.9985223,0.0006895515,0.0003129926,0.0001605709,0.0002191523,0.00009545299],"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":[0.004149829,0.001322767,0.4583835,0.0002375343,0.001429715,0.0006518743,0.0002344188,0.2858133,0.01785737,0.003112715,0.002551212,0.2242558],"study_design_scores_gemma":[0.00003698666,0.0003167795,0.0332481,0.0000145806,0.0002065506,0.0002070888,0.00003641702,0.9606182,0.002699904,0.002007222,0.0005667568,0.00004147025],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.794494,0.001274024,0.2013478,0.0004944417,0.00008309367,0.00008647802,0.0007271264,0.0004544146,0.001038702],"genre_scores_gemma":[0.9845955,0.000192639,0.0136663,0.00005569493,0.00005692469,0.0000487003,0.0006406447,0.00001638377,0.0007272448],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003025129,"threshold_uncertainty_score":0.0159986,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01709715488330401,"score_gpt":0.3092647617298288,"score_spread":0.2921676068465248,"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."}}