{"id":"W4413427465","doi":"10.1016/j.acepjo.2025.100240","title":"The Accuracy of Artificial Intelligence-Based Models Applied to 12-Lead Electrocardiograms for the Diagnosis of Acute Coronary Syndrome: A Systematic Review","year":2025,"lang":"en","type":"review","venue":"Journal of the American College of Emergency Physicians Open","topic":"ECG Monitoring and Analysis","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto General Hospital; University Health Network; University of Toronto","funders":"University of Toronto","keywords":"Acute coronary syndrome; Lead (geology); Cardiology; Computer science; Internal medicine; Artificial intelligence; Medicine; Geology; Myocardial infarction","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":[0.01688614,0.001893996,0.01128554,0.01018834,0.0005317263,0.003690499,0.002685181,0.002444609,0.002538054],"category_scores_gemma":[0.1018934,0.001568321,0.01565171,0.007004356,0.001060896,0.002887078,0.001447635,0.00163591,0.0002479711],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0035035,"about_ca_system_score_gemma":0.007945759,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008100796,"about_ca_topic_score_gemma":0.01583015,"domain_scores_codex":[0.9803488,0.009027033,0.006115833,0.00122688,0.003060048,0.0002214339],"domain_scores_gemma":[0.9089565,0.07555525,0.009990623,0.001159648,0.004066461,0.0002714698],"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":[0.0002900364,0.00002676606,0.001836076,0.9238878,0.03809695,0.00005885,0.0001161171,0.0004735963,0.00007496175,0.0001818989,0.000587487,0.03436932],"study_design_scores_gemma":[0.0004929788,0.0003658876,0.005766964,0.749954,0.2349258,0.0002847973,0.0001675354,0.001062262,0.0002167362,0.0004695203,0.006219694,0.00007377737],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.001662441,0.9969694,0.0003685604,0.0002084356,0.00009114652,0.0003150056,0.0002213131,0.00001295104,0.0001508467],"genre_scores_gemma":[0.04746108,0.9482825,0.002435779,0.0005145948,0.0001498895,0.00077929,0.0002928533,0.00001160535,0.00007224796],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.01688614,"threshold_uncertainty_score":0.08930355,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06570316900209376,"score_gpt":0.3847082673072088,"score_spread":0.319005098305115,"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."}}