{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001261594,0.0000910955,0.0001640902,0.001005246,0.0006913603,0.00003420443,0.000490143,0.0001435785,0.00004236836],"category_scores_gemma":[0.001376425,0.00008811822,0.00004488062,0.0004693438,0.0001017308,0.0006270874,0.0004204854,0.0009360311,0.00009574111],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001908704,"about_ca_system_score_gemma":0.0002083436,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001038308,"about_ca_topic_score_gemma":0.00001417361,"domain_scores_codex":[0.9980379,0.0002664423,0.001120556,0.00006782415,0.0003201482,0.0001870886],"domain_scores_gemma":[0.9970718,0.0003293373,0.0009709682,0.0002091958,0.001331901,0.00008680839],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002337238,0.00004871278,0.8910435,0.0001175868,0.00009152466,0.000005801034,0.006558403,0.01464132,0.0003029869,0.03818578,0.002244724,0.04652598],"study_design_scores_gemma":[0.0004892581,0.00008915812,0.02444513,0.0007081688,0.00001924124,0.00006362287,0.009232556,0.8977055,0.00007092121,0.01218028,0.05486235,0.0001338054],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9548199,0.0004458583,0.01488997,0.02753223,0.001181428,0.0002879705,0.00001791056,0.000405124,0.0004195782],"genre_scores_gemma":[0.9949951,0.0003965048,0.003485658,0.0008913265,0.0001328709,0.000004999657,0.00005453733,0.00000859515,0.00003043854],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8830642,"threshold_uncertainty_score":0.5317454,"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."}}