{"id":"W3110157010","doi":"10.1109/iccis49240.2020.9257700","title":"A Novel Approach to Classify Electrocardiogram Signals Using Deep Neural Networks","year":2020,"lang":"en","type":"article","venue":"","topic":"ECG Monitoring and Analysis","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Artificial intelligence; Process (computing); Convolutional neural network; Task (project management); Atrial fibrillation; Pattern recognition (psychology); Normal Sinus Rhythm; Rhythm; Artificial neural network; Sinus rhythm; Machine learning; Speech recognition; Engineering","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":[0.0003569511,0.001129426,0.0005656505,0.0008111901,0.0002366822,0.000714544,0.001130408,0.0009197132,0.001278233],"category_scores_gemma":[0.0008607554,0.0003413681,0.0006694372,0.0006575565,0.000191946,0.0008490935,0.0007608529,0.001298826,0.0008010822],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005389577,"about_ca_system_score_gemma":0.0005952992,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006586514,"about_ca_topic_score_gemma":0.009956455,"domain_scores_codex":[0.9997143,0.00003148321,0.00002469845,0.00009961443,0.00007072166,0.00005920851],"domain_scores_gemma":[0.9997861,0.00005192998,0.00002469959,0.00002487245,0.00009300349,0.00001945503],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002707975,0.0004418339,0.005980938,0.0001330723,0.0001919568,0.0002169062,0.00007182445,0.09971203,0.02075854,0.002462981,0.01086212,0.858897],"study_design_scores_gemma":[0.00001026187,0.00006594219,0.0009457732,0.00001597767,0.0000258206,0.00005636496,0.00001606723,0.9918348,0.003936763,0.001446326,0.001636229,0.000009736934],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08472834,0.003020473,0.8989304,0.001041907,0.0007019223,0.0001857557,0.001235327,0.004748887,0.005407026],"genre_scores_gemma":[0.7357507,0.001666669,0.2404889,0.0009995712,0.0004394204,0.0001999993,0.00466468,0.0001339807,0.01565613],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006586514,"threshold_uncertainty_score":0.01309639,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06176295701635784,"score_gpt":0.29254582760339,"score_spread":0.2307828705870321,"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."}}