biostudies-literatureSvennberg EBritish Heart FoundationAEINHLBI NIH HHSSwedish Heart and Lung AssociationHealthcare Innovation FundSwedish Research CouncilNIHEuropean UnionDutch Research Council (NWO)National Institute for Health and Care ResearchNIH HHSStockholm County CouncilMCINeuaf071https://www.ebi.ac.uk/biostudies/studies/S-EPMC12123071biostudies-literatureUnknown27(5)<h4>Aims</h4>Artificial intelligence (AI) has the potential to transform cardiac electrophysiology (EP), particularly in arrhythmia detection, procedural optimization, and patient outcome prediction. However, a standardized approach to reporting and understanding AI-related research in EP is lacking. This scientific statement aims to develop and apply a checklist for AI-related research reporting in EP to enhance transparency, reproducibility, and understandability in the field.<h4>Methods and results</h4>An AI checklist specific to EP was developed with expert input from the writing group and voted on using a modified Delphi process, leading to the development of a 29-item checklist. The checklist was subsequently applied to assess reporting practices to identify areas where improvements Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of CardiologyState of the Art of Artificial Intelligence in Clinical Electrophysiology in 2025: A Scientific Statement of the European Heart Rhythm Association (EHRA) of the ESC, the Heart Rhythm Society (HRS), and the ESC Working Group on E-Cardiology.PMC12123071PID2023-148975OB-I00R01HL174440R01 HL174440NIHR204553R01 HL166759RE/24/13003DNR 2022-01466R01HL166759HI/C2/24/360038CNS2023-143599PID2021-128972OA-I00Millet JNarayan SMHindricks GTrayanova NBarker JErnst STjong FVYDuncker DChatterjee NAMan SHConte GZorzi ADiederichsen SZRamirez JEngelhardt SLinz DGarcia RHan JKCasado-Arroyo RSingh JPMahtani AUSvennberg ENoseworthy PANg GACaiani EGTfelt Hansen JGhanbari HFriedman PfalseState of the Art of Artificial Intelligence in Clinical Electrophysiology in 2025: A Scientific Statement of the European Heart Rhythm Association (EHRA) of the ESC, the Heart Rhythm Society (HRS), and the ESC Working Group on E-Cardiology.<h4>Aims</h4>Artificial intelligence (AI) has the potential to transform cardiac electrophysiology (EP), particularly in arrhythmia detection, procedural optimization, and patient outcome prediction. However, a standardized approach to reporting and understanding AI-related research in EP is lacking. This scientific statement aims to develop and apply a checklist for AI-related research reporting in EP to enhance transparency, reproducibility, and understandability in the field.<h4>Methods and results</h4>An AI checklist specific to EP was developed with expert input from the writing group and voted on using a modified Delphi process, leading to the development of a 29-item checklist. The checklist was subsequently applied to assess reporting practices to identify areas where improvements 2025-01-01T00:00:00Z2025 May2026-06-01T11:39:48.924Z2026-04-08T11:55:46.18ZS-EPMC121230714016365110.1093/europace/euaf071