{"id":"W4205747946","doi":"10.23919/cinc53138.2021.9662908","title":"Arrhythmia Classification of Reduced-Lead Electrocardiograms by Scattering-Recurrent Networks","year":2021,"lang":"en","type":"article","venue":"2021 Computing in Cardiology (CinC)","topic":"ECG Monitoring and Analysis","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Artificial intelligence; Test set; Computer science; Pattern recognition (psychology); Classifier (UML); Deep learning; Convolution (computer science); Matthews correlation coefficient; Machine learning; Algorithm; Support vector machine; Artificial neural network","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":[0.0005505762,0.0002018831,0.0008972373,0.0001536824,0.0000696151,0.00001526335,0.0001074467,0.000227704,0.00001024625],"category_scores_gemma":[0.0001491748,0.0002077706,0.0003695279,0.0007843173,0.0001042317,0.0000231988,0.00009514033,0.0005336856,0.00001011641],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001443555,"about_ca_system_score_gemma":0.0001058116,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003352771,"about_ca_topic_score_gemma":0.000004247029,"domain_scores_codex":[0.9979427,0.0003151536,0.0005616408,0.0005526296,0.0001941905,0.0004336829],"domain_scores_gemma":[0.9988284,0.000175776,0.0001774602,0.0005187376,0.000211459,0.00008814527],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001125658,0.0001217182,0.5804437,0.0001623778,0.001078086,0.0003702278,0.0001638819,0.01592679,0.1349372,0.00004471404,0.004932949,0.2617058],"study_design_scores_gemma":[0.003607364,0.0007402563,0.6540661,0.00167743,0.001259391,0.001469319,0.000957071,0.2972063,0.02563351,0.00009073996,0.01225529,0.001037244],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9650084,0.0062387,0.02515475,0.0008483576,0.0009396563,0.0001285363,0.000004127824,0.00005392492,0.001623499],"genre_scores_gemma":[0.9963444,0.0004198023,0.001140765,0.00005320154,0.001688353,0.000008535897,0.0001784369,0.00002498468,0.0001415324],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2812795,"threshold_uncertainty_score":0.8472638,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01554405605063035,"score_gpt":0.2832420263602359,"score_spread":0.2676979703096055,"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."}}