{"id":"W4415819494","doi":"10.3390/jpm15110532","title":"Artificial Intelligence in Cardiac Electrophysiology: A Comprehensive Review","year":2025,"lang":"en","type":"review","venue":"Journal of Personalized Medicine","topic":"ECG Monitoring and Analysis","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Surgical Specialties (Canada)","funders":"","keywords":"Atrial flutter; Clinical Practice; Deep learning; Atrial fibrillation; Narrative review; Cardiac electrophysiology; Applications of artificial intelligence","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001107279,0.000486004,0.008016514,0.001151019,0.00003963218,0.00000550503,0.0002823784,0.0002867315,0.0002793215],"category_scores_gemma":[0.001474026,0.0003019787,0.001801547,0.001685208,0.0002405691,0.00003721077,0.00004178391,0.001661027,0.00001673053],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003754179,"about_ca_system_score_gemma":0.001279216,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002185541,"about_ca_topic_score_gemma":5.57746e-7,"domain_scores_codex":[0.9957633,0.0005669539,0.002318885,0.0003400597,0.0006545625,0.0003562086],"domain_scores_gemma":[0.9966635,0.0008322194,0.001315765,0.0003535667,0.0006007883,0.0002341327],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007996839,0.00008933835,0.000003382106,0.1071492,0.0009485052,0.0004513419,0.00005826168,2.030083e-7,0.00003107367,0.00004606647,0.003993561,0.887149],"study_design_scores_gemma":[0.0001548757,0.0004709381,0.000002738803,0.3632268,0.008961118,0.0002501021,0.00009435104,0.000002760416,0.00000197211,0.00006854701,0.6266273,0.0001385388],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000004614596,0.9966574,0.0001196444,0.001628827,0.0007705417,0.0005162958,0.000006339731,0.00001092143,0.0002854622],"genre_scores_gemma":[0.000003095664,0.9957806,0.0005009256,0.0006474975,0.002318029,0.00002130342,0.00004239447,0.00002997102,0.0006561939],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.8870105,"threshold_uncertainty_score":0.9999433,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08345179510726768,"score_gpt":0.434442039151718,"score_spread":0.3509902440444503,"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."}}