{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001108638,0.0003433317,0.002066747,0.0007058788,0.0001120139,0.00004821974,0.0002030835,0.0003487547,0.0006822362],"category_scores_gemma":[0.000611329,0.0002505535,0.0002753497,0.0004930267,0.0003009367,0.00007512872,0.00007157683,0.001854158,0.00007224211],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004832908,"about_ca_system_score_gemma":0.0007733477,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001860582,"about_ca_topic_score_gemma":0.00003874695,"domain_scores_codex":[0.9966115,0.0002667563,0.001978647,0.0004205766,0.0003434722,0.0003790756],"domain_scores_gemma":[0.997988,0.0005598505,0.0005178094,0.0002879157,0.0002458023,0.0004005942],"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":[0.00001446879,0.00005329411,0.0002658904,0.001939706,0.0001146478,0.0002540319,0.0002519411,5.93624e-7,0.000001321665,0.0003345343,0.001156469,0.9956131],"study_design_scores_gemma":[0.00002038095,0.0003386784,0.00002205639,0.0366398,0.0005695528,0.01715044,0.001872688,0.00001081603,0.000006614944,0.00235148,0.9408278,0.0001896725],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00004505199,0.9885655,0.006551133,0.001200823,0.001353304,0.0007041352,0.000005023905,0.00001527528,0.00155972],"genre_scores_gemma":[0.000390748,0.9918371,0.000229602,0.000244991,0.006669102,0.0001283994,0.0000398394,0.00003789818,0.0004223006],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9954234,"threshold_uncertainty_score":0.9999947,"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."}}