{"id":"W4224437668","doi":"10.3390/s22093283","title":"Inter-Patient Congestive Heart Failure Detection Using ECG-Convolution-Vision Transformer Network","year":2022,"lang":"en","type":"article","venue":"Sensors","topic":"ECG Monitoring and Analysis","field":"Medicine","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Heart failure; Cardiology; Transformer; Convolution (computer science); Internal medicine; Medicine; Computer science; Artificial intelligence; Engineering; Electrical engineering; Voltage; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004794649,0.0005604174,0.0004203604,0.000516625,0.0001985795,0.0003594048,0.0005455057,0.0004791472,0.000679341],"category_scores_gemma":[0.0009362355,0.0002083953,0.0004395818,0.00030342,0.000217845,0.0005237073,0.0004461095,0.0004002305,0.0001358733],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005997862,"about_ca_system_score_gemma":0.0005142493,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006377138,"about_ca_topic_score_gemma":0.00570844,"domain_scores_codex":[0.9997714,0.00002904402,0.00001262826,0.00007486827,0.00006825439,0.00004375552],"domain_scores_gemma":[0.9998044,0.00006163969,0.00002530632,0.0000190527,0.0000702531,0.00001946203],"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":[0.0009887794,0.0004920402,0.02418932,0.0001210721,0.0002000361,0.000603478,0.0001122659,0.2978165,0.05886258,0.002195728,0.002748547,0.6116697],"study_design_scores_gemma":[0.00000788644,0.00007052186,0.002561754,0.000003182149,0.00001935785,0.0001183547,0.000007246155,0.9903562,0.006307207,0.0003679089,0.0001731711,0.000007261568],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.335243,0.0006844654,0.6584328,0.0003100917,0.0001638822,0.0001180494,0.0002175037,0.001588376,0.003241969],"genre_scores_gemma":[0.9749271,0.000156809,0.02349195,0.00008029072,0.0000179085,0.00002606335,0.0001484335,0.00001447401,0.001136937],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006377138,"threshold_uncertainty_score":0.01267999,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01184152596732633,"score_gpt":0.262224335650622,"score_spread":0.2503828096832957,"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."}}