{"id":"W4412037924","doi":"10.18280/isi.300501","title":"Detection of Heart Disease Using Binary Classification Machine Learning Model","year":2025,"lang":"en","type":"article","venue":"Ingénierie des systèmes d information","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Binary classification; Computer science; Binary number; Artificial intelligence; Machine learning; Pattern recognition (psychology); Support vector machine; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001799009,0.0007581168,0.0008244731,0.00280584,0.0003433661,0.001291302,0.000806626,0.0008780625,0.001415083],"category_scores_gemma":[0.005433593,0.0001553669,0.0007828175,0.00130333,0.000206635,0.0009583607,0.0004895623,0.0006425559,0.001244981],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004919572,"about_ca_system_score_gemma":0.000685555,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006374884,"about_ca_topic_score_gemma":0.0038328,"domain_scores_codex":[0.9987668,0.0003677333,0.0001416064,0.0002799185,0.0003040017,0.0001400879],"domain_scores_gemma":[0.9979675,0.001048986,0.0002217375,0.0001836583,0.0005235337,0.00005450791],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008869557,0.00121815,0.1520551,0.0003998395,0.0003245658,0.0004103132,0.0001759503,0.1323263,0.008848727,0.003648712,0.01581188,0.6838935],"study_design_scores_gemma":[0.00002574724,0.0001912195,0.01840178,0.00006154557,0.00005277895,0.0002502418,0.00007897597,0.9716612,0.003532755,0.003556336,0.002148155,0.00003918676],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3833037,0.002116511,0.5943919,0.001097516,0.0004506134,0.0005482914,0.005650611,0.004144815,0.008295949],"genre_scores_gemma":[0.8596149,0.0004545103,0.1319579,0.0001938096,0.0001124583,0.0002822323,0.004982554,0.00004092793,0.00236083],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006374884,"threshold_uncertainty_score":0.01267558,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1051175393826718,"score_gpt":0.4037364619685792,"score_spread":0.2986189225859073,"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."}}