{"id":"W4399891523","doi":"10.18280/ria.380329","title":"Assessment of Cardiovascular Disease Using Machine Learning","year":2024,"lang":"fr","type":"article","venue":"Revue d intelligence artificielle","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Disease; Computer science; Artificial intelligence; Medicine; Machine learning; Internal medicine","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":[0.002723014,0.0009606092,0.0009517777,0.00304058,0.0003074554,0.001544395,0.001021609,0.001052156,0.001487828],"category_scores_gemma":[0.01303444,0.0002190275,0.000904255,0.001609137,0.0003455131,0.001408084,0.0008365242,0.001381428,0.0007832522],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006073409,"about_ca_system_score_gemma":0.000700094,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003559979,"about_ca_topic_score_gemma":0.003740808,"domain_scores_codex":[0.9984628,0.0005798858,0.0001647424,0.0003320216,0.0003840233,0.00007665984],"domain_scores_gemma":[0.9941549,0.003742788,0.0008101169,0.0004667628,0.0006768225,0.0001486619],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002861776,0.0006308621,0.2750958,0.0003513804,0.000515544,0.0002469498,0.0001232582,0.3553413,0.001901845,0.004302606,0.00915374,0.3520505],"study_design_scores_gemma":[0.00001196626,0.0001757019,0.02371317,0.0000782544,0.00005301172,0.0001572205,0.00007022584,0.9650403,0.001161121,0.007476825,0.002025872,0.00003628044],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.263651,0.0048234,0.7080764,0.003693844,0.0004119348,0.0004719344,0.009136634,0.002724227,0.007010634],"genre_scores_gemma":[0.8959929,0.001502053,0.0958024,0.0003923292,0.000291948,0.0002243767,0.004606397,0.00004427434,0.00114342],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003559979,"threshold_uncertainty_score":0.01440084,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1855878970557512,"score_gpt":0.4554441810071031,"score_spread":0.2698562839513519,"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."}}