{"id":"W3134665742","doi":"10.1016/j.cjca.2021.02.020","title":"Machine Learning Compared With Conventional Statistical Models for Predicting Myocardial Infarction Readmission and Mortality: A Systematic Review","year":2021,"lang":"en","type":"review","venue":"Canadian Journal of Cardiology","topic":"Acute Myocardial Infarction Research","field":"Medicine","cited_by":63,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Rehabilitation Institute; Women's College Hospital; Institute for Work & Health; Ted Rogers Centre for Heart Research; Institute for Clinical Evaluative Sciences; Toronto General Hospital; University Health Network; University of Toronto","funders":"Canadian Institutes of Health Research; University of Toronto; Ontario Ministry of Health and Long-Term Care; Institute for Clinical Evaluative Sciences; Heart and Stroke Foundation of Canada","keywords":"Medicine; Myocardial infarction; Internal medicine; Cardiology; Intensive care medicine; Machine learning","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.01016692,0.002061059,0.01550426,0.003774065,0.0003987362,0.002423849,0.002508833,0.002075454,0.003607589],"category_scores_gemma":[0.03445068,0.001236873,0.01844837,0.004575154,0.0008615625,0.002998638,0.001461382,0.002491566,0.0003010985],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001773314,"about_ca_system_score_gemma":0.003490748,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007373866,"about_ca_topic_score_gemma":0.01943279,"domain_scores_codex":[0.9936422,0.002975368,0.001732294,0.0006670498,0.0008542101,0.0001288715],"domain_scores_gemma":[0.9713027,0.02480957,0.002476175,0.0003775715,0.000880931,0.0001531217],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","study_design_scores_codex":[0.002425448,0.00006625291,0.002997735,0.7089068,0.2122598,0.00008034113,0.0001186564,0.000893918,0.0001612832,0.0002673843,0.001505704,0.07031671],"study_design_scores_gemma":[0.002721782,0.0008631292,0.007467884,0.1616482,0.8197863,0.0001867859,0.0001668804,0.001550971,0.0001747528,0.0009613065,0.004381104,0.00009096455],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00166373,0.9973471,0.0003980931,0.0001008511,0.0000772193,0.0001220063,0.0001973837,0.00001488277,0.00007880963],"genre_scores_gemma":[0.05363768,0.9427834,0.002195196,0.0004940382,0.0001583636,0.0002903594,0.0003036624,0.00001684424,0.0001204585],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.01550426,"threshold_uncertainty_score":0.05376852,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08487553238248224,"score_gpt":0.3716521719093551,"score_spread":0.2867766395268729,"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."}}