{"id":"W4384210476","doi":"10.5958/2347-7202.2023.00004.x","title":"Heart disease prediction using machine learning","year":2023,"lang":"en","type":"article","venue":"JIMS8I - International Journal of Information Communication and Computing Technology","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Forces College","funders":"","keywords":"Computer science; Artificial intelligence; Machine learning; Disease; Medicine; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"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":[0.001537381,0.00085354,0.0009323317,0.003506513,0.0002938686,0.00123754,0.0007845463,0.0009999003,0.001661408],"category_scores_gemma":[0.006354168,0.0002582653,0.001112083,0.001564042,0.0002078565,0.0007332395,0.0005207103,0.001101582,0.001255027],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005269598,"about_ca_system_score_gemma":0.0007135161,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007960511,"about_ca_topic_score_gemma":0.005773958,"domain_scores_codex":[0.9991392,0.0002352786,0.0001096448,0.0002276544,0.0001914174,0.00009675254],"domain_scores_gemma":[0.996821,0.001803608,0.0004054584,0.0001745107,0.0006365132,0.0001589843],"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":[0.0006235215,0.000943546,0.3019358,0.0003612335,0.0005979587,0.000676106,0.00008404859,0.2772108,0.001559367,0.001445711,0.01594176,0.39862],"study_design_scores_gemma":[0.00001975135,0.000128399,0.01864786,0.00005636497,0.00005329301,0.0002109159,0.00002874525,0.9751923,0.0009122717,0.003377075,0.001349639,0.00002349258],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5290977,0.01094298,0.4237657,0.003330802,0.0008086192,0.0004960365,0.01661006,0.005685686,0.009262372],"genre_scores_gemma":[0.938963,0.001547013,0.04809113,0.0002727384,0.0003701659,0.0001528544,0.00891353,0.00004434234,0.001645322],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007960511,"threshold_uncertainty_score":0.01582831,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08833279982864652,"score_gpt":0.4556932008833723,"score_spread":0.3673604010547258,"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."}}