{"id":"W4401808192","doi":"10.1109/atsip62566.2024.10638983","title":"Automated System Classification of ECG Heartbeat based on Support Vector Machine and Convolutional Neural Network","year":2024,"lang":"en","type":"article","venue":"","topic":"ECG Monitoring and Analysis","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université TÉLUQ","funders":"","keywords":"Heartbeat; Computer science; Support vector machine; Convolutional neural network; Artificial intelligence; Pattern recognition (psychology); Artificial neural network; Speech recognition; Machine learning","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":[0.0001736535,0.00008251346,0.0001892884,0.00009139762,0.00003831421,0.00001540304,0.00002000219,0.0000489568,0.00009856976],"category_scores_gemma":[0.00001459402,0.00006049631,0.00006638007,0.0002459912,0.0000304651,0.00002350305,0.000006452243,0.00008828977,0.00002146581],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005178314,"about_ca_system_score_gemma":0.00005455773,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005055217,"about_ca_topic_score_gemma":0.000002768714,"domain_scores_codex":[0.999301,0.00003239724,0.0001958224,0.0001743022,0.0001841823,0.0001123166],"domain_scores_gemma":[0.9996273,0.00008886955,0.00002704313,0.0001330696,0.00004915143,0.00007456643],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007236906,0.0004556566,0.8560661,0.004685075,0.000887845,0.0002627317,0.0001470834,0.01041815,0.03536918,0.008252494,0.06798892,0.01474306],"study_design_scores_gemma":[0.0002440094,0.0001614976,0.144566,0.0002174554,0.0001215624,0.00001933841,0.00002248022,0.8538104,0.0002624428,0.000001336391,0.0005287793,0.0000447438],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9830505,0.001086984,0.002225433,0.004810646,0.0009504604,0.0003257309,0.00004812592,0.002076967,0.005425117],"genre_scores_gemma":[0.9976209,0.000004910539,0.0006271616,0.00006419557,0.0002509799,0.000006467456,0.0001035653,0.00001116568,0.001310668],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8433923,"threshold_uncertainty_score":0.2466968,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01923855346480033,"score_gpt":0.2849216929524496,"score_spread":0.2656831394876493,"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."}}