{"id":"W2152408591","doi":"10.1109/tmi.2009.2021429","title":"Mapping of Cardiac Electrophysiology Onto a Dynamic Patient-Specific Heart Model","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Medical Imaging","topic":"Cardiac Arrhythmias and Treatments","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University; Lawson Health Research Institute; London Health Sciences Centre; Robarts Clinical Trials","funders":"Canadian Institutes of Health Research; St. Jude Medical","keywords":"Cardiac electrophysiology; Computer science; Sinus rhythm; Visualization; Normal Sinus Rhythm; Electrophysiology; Atrial fibrillation; Cardiac monitoring; Cardiac arrhythmia; Artificial intelligence; Medicine; Cardiology; Internal medicine","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003914879,0.0003562823,0.0003643236,0.0003650608,0.000133074,0.0009214964,0.0005109227,0.0004845158,0.002048382],"category_scores_gemma":[0.002516879,0.0002013347,0.0004006536,0.0002564723,0.0003037346,0.0007854594,0.0009579997,0.000437264,0.0004822118],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001488944,"about_ca_system_score_gemma":0.000406027,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004587909,"about_ca_topic_score_gemma":0.0005239964,"domain_scores_codex":[0.9996612,0.00008248065,0.00002656625,0.00007717786,0.000134284,0.00001821984],"domain_scores_gemma":[0.9993717,0.0002592694,0.00005551328,0.0001743106,0.00009658006,0.00004262964],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005490399,0.0003184036,0.007721553,0.0003484565,0.0001169586,0.001193727,0.001168117,0.1059366,0.4829592,0.007124799,0.004555512,0.3880077],"study_design_scores_gemma":[0.0001112926,0.001516026,0.01652084,0.00008556392,0.0001488173,0.00575641,0.0004465972,0.7132083,0.2164291,0.007507842,0.03808704,0.0001820647],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0666636,0.0001186239,0.9294324,0.0001625259,0.00005170751,0.0001115222,0.0001337692,0.001648491,0.001677294],"genre_scores_gemma":[0.6031953,0.0005821024,0.3922492,0.0002336089,0.00006107421,0.0002791625,0.0003742607,0.0002762249,0.002749062],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002048382,"threshold_uncertainty_score":0.006852508,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007850827175568113,"score_gpt":0.2609137838564614,"score_spread":0.2530629566808933,"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."}}