{"id":"W3204921442","doi":"10.1111/imj.15562","title":"Artificial intelligence in cardiology: fundamentals and applications","year":2021,"lang":"en","type":"review","venue":"Internal Medicine Journal","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Workflow; Medicine; Artificial intelligence; Modalities; Artificial neural network; Field (mathematics); Set (abstract data type); Machine learning; Health care; Patient care; Computer science","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":[0.001382253,0.0008924889,0.001236156,0.002819493,0.0004239251,0.002205965,0.00111706,0.00217693,0.004604394],"category_scores_gemma":[0.002631601,0.0003489991,0.0007360876,0.003308614,0.001551465,0.002364514,0.001175771,0.003889978,0.00255297],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001161154,"about_ca_system_score_gemma":0.001814769,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001486654,"about_ca_topic_score_gemma":0.001473787,"domain_scores_codex":[0.9991997,0.0001946151,0.000120558,0.00009276369,0.0003443511,0.00004809016],"domain_scores_gemma":[0.9980354,0.001336439,0.0001274666,0.00005972091,0.0003605133,0.00008054404],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002719255,0.00006386195,0.0002449615,0.0123478,0.00007799095,0.0001413747,0.0001345681,0.0005351036,0.0004339971,0.02192333,0.03692669,0.9271431],"study_design_scores_gemma":[0.00001013534,0.00006286211,0.001139333,0.0103537,0.00005077028,0.0009163851,0.0001152959,0.0002301663,0.000170127,0.02103874,0.9658833,0.00002940141],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00007490615,0.9955343,0.000421631,0.001028571,0.0003284907,0.00001015857,0.00001141254,0.00001050337,0.002580053],"genre_scores_gemma":[0.0008894493,0.9968171,0.0005920816,0.0005395344,0.0005444961,0.0000147228,0.00001844175,0.000003472513,0.0005807379],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.004604394,"threshold_uncertainty_score":0.01540327,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3546461484877277,"score_gpt":0.5403267777895113,"score_spread":0.1856806293017836,"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."}}