{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002184084,0.0003502945,0.005497496,0.0004838923,0.0001909139,0.00004863235,0.0001326344,0.0003238523,0.00002702277],"category_scores_gemma":[0.002283939,0.0002519464,0.0007985635,0.0002516438,0.0002263209,0.00009145693,0.00003001782,0.001208059,0.000001963872],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004663352,"about_ca_system_score_gemma":0.005564971,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002878436,"about_ca_topic_score_gemma":0.00004939596,"domain_scores_codex":[0.996015,0.001356467,0.001413631,0.0003402996,0.0004444491,0.000430143],"domain_scores_gemma":[0.9959502,0.0007298284,0.0008511712,0.0002702561,0.001097243,0.001101261],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009830319,0.000006285459,0.0005260593,0.9486457,0.0141045,0.001033156,0.00003818932,0.0006228865,2.621787e-7,0.000721983,0.01480782,0.01939493],"study_design_scores_gemma":[0.0007351051,0.0004947968,0.00002436557,0.2925142,0.01560802,0.01606605,0.00004019463,0.0004527986,2.241223e-8,0.00004137333,0.6738193,0.0002037565],"study_design_candidate":"systematic_review","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000001608512,0.9767831,0.01957392,0.0004598018,0.0002953612,0.00210941,0.0003483405,0.000009525494,0.0004189456],"genre_scores_gemma":[0.0001772449,0.9968725,0.000626731,0.0003185461,0.00084003,0.0001475454,0.0008357424,0.00006167033,0.0001199961],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.6590115,"threshold_uncertainty_score":0.9999933,"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."}}