{"id":"W4408185936","doi":"10.2196/64349","title":"The Role of AI in Cardiovascular Event Monitoring and Early Detection: Scoping Literature Review","year":2025,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Event (particle physics); Computer science; Medicine; Data science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.001984117,0.00009430983,0.0003403138,0.00008261829,0.0003631409,0.00001268285,0.0001952552,0.0002536062,0.000009214909],"category_scores_gemma":[0.0009941297,0.00006405585,0.00008362604,0.0005045572,0.00008745005,0.0001581645,0.0001565791,0.001267775,0.00001099163],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009161995,"about_ca_system_score_gemma":0.0003792948,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001522276,"about_ca_topic_score_gemma":0.0001220156,"domain_scores_codex":[0.9975939,0.000280917,0.001261385,0.00007399828,0.0004989989,0.000290765],"domain_scores_gemma":[0.9985917,0.0005790266,0.000160308,0.0003273717,0.0002281077,0.0001135541],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"systematic_review","study_design_scores_codex":[0.00002912256,0.0000232675,0.0895647,0.04053533,0.00008365567,0.000006158245,0.02556526,0.000007693856,0.000008729948,0.002436896,0.0002302342,0.8415089],"study_design_scores_gemma":[0.0006245807,0.0001681688,0.02958542,0.7962438,0.000100097,0.00001347129,0.04467336,0.008159515,0.001723098,0.00763655,0.1106518,0.0004200909],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.4060698,0.5779624,0.0009569277,0.004442735,0.002151432,0.004738546,0.00000365008,0.00009152073,0.003582973],"genre_scores_gemma":[0.930603,0.06721144,0.0001128173,0.001217096,0.0002298102,0.0005482423,0.000001270241,0.000009060541,0.00006726645],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8410888,"threshold_uncertainty_score":0.5507923,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0362529481417266,"score_gpt":0.4516073148730462,"score_spread":0.4153543667313196,"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."}}