State 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 in e-Cardiology.
E Svennberg, J K Han, E G Caiani, S Engelhardt, S Ernst, P Friedman, R Garcia, H Ghanbari, G Hindricks, S H Man, J Millet, S M Narayan, G A Ng, P A Noseworthy, F V Y Tjong, J Ramírez, J P Singh, N Trayanova, D Duncker
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引用次数: 0
Abstract
Aim: 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.
Methods: 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 could be made and provide an overview of the state of the art in AI-related EP research in three domains from May 2021 until May 2024: atrial fibrillation management, sudden cardiac death (SCD), and EP lab applications.
Results: The EHRA AI checklist was applied to 31 studies in atrial fibrillation management, 18 studies in SCD, and 6 studies in EP lab applications. Results differed between the different domains, but in no domain reporting of a specific item exceeded 55 % of included papers. Key areas such as trial registration, participant details, data handling, and training performance were underreported (<20%). The checklist application highlighted areas where reporting practices could be improved to promote clearer, more comprehensive AI research in EP.
Conclusion: The EHRA AI checklist provides a structured framework for reporting AI research in EP. Its use can improve understanding but also enhance the reproducibility and transparency of AI studies, fostering more robust and reliable integration of AI into clinical EP practice.
期刊介绍：
EP - Europace - European Journal of Pacing, Arrhythmias and Cardiac Electrophysiology of the European Heart Rhythm Association of the European Society of Cardiology. The journal aims to provide an avenue of communication of top quality European and international original scientific work and reviews in the fields of Arrhythmias, Pacing and Cellular Electrophysiology. The Journal offers the reader a collection of contemporary original peer-reviewed papers, invited papers and editorial comments together with book reviews and correspondence.
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