{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005132181,0.0001689895,0.0003037796,0.0003636344,0.00006846933,0.0000172155,0.0001886874,0.00003821646,0.000007455745],"category_scores_gemma":[0.0002618869,0.0001423322,0.00006053194,0.0005019855,0.0002116965,0.0001040296,0.0001304262,0.0002190255,0.000005741773],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009251443,"about_ca_system_score_gemma":0.000468001,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003121275,"about_ca_topic_score_gemma":1.915495e-7,"domain_scores_codex":[0.9980387,0.00004907247,0.0003741958,0.0005449748,0.0006002436,0.000392809],"domain_scores_gemma":[0.9991331,0.00002798066,0.0001101643,0.0002311221,0.00004477129,0.0004529175],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001494622,0.0006499832,0.9133431,0.0001979525,0.00003995158,0.0001143916,0.00164927,0.002068976,0.02375218,0.00001657543,0.006605104,0.05006785],"study_design_scores_gemma":[0.002373104,0.0003408987,0.5104469,0.001030003,0.00007200192,0.00001249751,0.0001682322,0.4804669,0.004041159,0.00003112035,0.0007747682,0.0002424337],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9720419,0.0003874726,0.02390844,0.0009209004,0.001151438,0.001268622,0.000008586915,0.00004051309,0.0002720954],"genre_scores_gemma":[0.9496188,0.00003070378,0.04908537,0.001051691,0.00002124026,0.00004606383,0.000008640608,0.00002100642,0.0001165476],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4783979,"threshold_uncertainty_score":0.5804139,"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."}}