{"id":"W2105776665","doi":"10.2196/medinform.4397","title":"A Telesurveillance System With Automatic Electrocardiogram Interpretation Based on Support Vector Machine and Rule-Based Processing","year":2015,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"ECG Monitoring and Analysis","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Taiwan University; National Taiwan University Hospital","keywords":"Artificial intelligence; Computer science; Support vector machine; Telehealth; Workload; Machine learning; Atrial flutter; Telemedicine; Pattern recognition (psychology); Atrial fibrillation; Data mining; Medicine; Health care; Cardiology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007208312,0.0007312026,0.0009497341,0.001026434,0.0002332359,0.0005571343,0.001016432,0.0007280116,0.001961849],"category_scores_gemma":[0.001352904,0.0002547192,0.0003795211,0.0004191831,0.0001935691,0.0007589235,0.0005751163,0.000335073,0.0008923937],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000266547,"about_ca_system_score_gemma":0.0003277486,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001236382,"about_ca_topic_score_gemma":0.0007597799,"domain_scores_codex":[0.9992421,0.00009909741,0.00008369754,0.0002375481,0.0002728761,0.00006471777],"domain_scores_gemma":[0.9991803,0.0001635457,0.00007864051,0.0001299158,0.0003806303,0.00006693275],"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":[0.002042665,0.001298953,0.02543058,0.0002861963,0.0003048188,0.001545893,0.0002851043,0.01547723,0.1990205,0.0008331306,0.009788986,0.743686],"study_design_scores_gemma":[0.0003573488,0.0024446,0.03265061,0.00005830655,0.0004054861,0.002328651,0.0001420565,0.8320008,0.1209394,0.0009224196,0.007547138,0.0002032469],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4046014,0.0006862059,0.5666612,0.0002644802,0.0002494567,0.0005307582,0.0005181441,0.02337338,0.003115005],"genre_scores_gemma":[0.8409773,0.000232513,0.1535862,0.0003182788,0.0001433667,0.0002683495,0.001130318,0.0001296156,0.003214022],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001961849,"threshold_uncertainty_score":0.006563067,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008699682535357755,"score_gpt":0.2752628213911485,"score_spread":0.2665631388557908,"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."}}