{"id":"W2889107381","doi":"10.1038/s41380-018-0228-9","title":"Using structural MRI to identify bipolar disorders – 13 site machine learning study in 3020 individuals from the ENIGMA Bipolar Disorders Working Group","year":2018,"lang":"en","type":"review","venue":"Molecular Psychiatry","topic":"Bipolar Disorder and Treatment","field":"Medicine","cited_by":175,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"National Institute on Aging; European Regional Development Fund; Helse Sør-Øst RHF; National Medical Research Council; Medical Research Council; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; Nova Scotia Health Research Foundation; University of Cape Town; Westfälische Wilhelms-Universität Münster; Dalhousie University; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Ministerio de Economía y Competitividad; Norges Forskningsråd; National Institute of Mental Health; Fondation pour la Recherche Médicale; Departament d'Innovació, Universitats i Empresa, Generalitat de Catalunya; Generalitat de Catalunya; National Health and Medical Research Council; Fundação de Amparo à Pesquisa do Estado de São Paulo; NIH Clinical Center; Agence Nationale de la Recherche; European Commission; National Alliance for Research on Schizophrenia and Depression; Centro de Investigación Biomédica en Red de Salud Mental; Departamento Administrativo de Ciencia, Tecnología e Innovación (COLCIENCIAS); Deutsche Forschungsgemeinschaft; Instituto de Salud Carlos III; National Research Foundation; South African Medical Research Council; National Institutes of Health; Fondation de l'Avenir pour la Recherche Médicale Appliquée","keywords":"Neuroimaging; Kappa; Bipolar disorder; Medicine; Odds; Artificial intelligence; Identification (biology); Psychology; Machine learning; Cognition; Logistic regression; Internal medicine; Psychiatry; Computer science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003277675,0.0006995525,0.0009925781,0.0006925958,0.0006046693,0.0008650912,0.0004383735,0.0006424574,0.001024659],"category_scores_gemma":[0.005686877,0.0006390903,0.001464734,0.0008414492,0.0003566487,0.0003740223,0.0006190673,0.0006114484,0.0003077472],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003144946,"about_ca_system_score_gemma":0.0002118583,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005349712,"about_ca_topic_score_gemma":0.00941496,"domain_scores_codex":[0.9984881,0.0006667485,0.00013708,0.0005154256,0.0001188377,0.00007381855],"domain_scores_gemma":[0.9980843,0.0006470114,0.0004184094,0.0004703696,0.0002770402,0.0001028627],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004217757,0.0002005709,0.9698766,0.0001864564,0.00767677,0.0001598771,0.0004423661,0.0004744221,0.002115975,0.00008959562,0.0008601385,0.01369955],"study_design_scores_gemma":[0.0003815121,0.0008241156,0.9891309,0.00008336197,0.005916477,0.0003844193,0.0001894087,0.001693405,0.0003797839,0.0003350427,0.000658448,0.00002318117],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9971942,0.001322979,0.0007270862,0.00004009781,0.00001453875,0.00003594948,0.0004068083,0.00001405389,0.0002443017],"genre_scores_gemma":[0.9979175,0.0002957081,0.0005909014,0.00005575836,0.00001749592,0.0000345536,0.000933341,0.00001297617,0.0001418537],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005349712,"threshold_uncertainty_score":0.01733422,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02909606754151366,"score_gpt":0.3466118960569004,"score_spread":0.3175158285153867,"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."}}