Artificial intelligence applications in atrial fibrillation are rapidly developing, as shown by a bibliometric analysis of 912 publications highlighting diagnosis, ablation, and risk management.
This bibliometric analysis maps the rapidly growing landscape of AI applications in atrial fibrillation, identifying key trends such as AI-ECG diagnosis and AI-assisted ablation.
Background: In the study of atrial fibrillation (AF), a prevalent cardiac arrhythmia, the utilization of artificial intelligence (AI) in diagnostic and therapeutic strategies holds the potential to address existing limitations. This research employs bibliometrics to objectively investigate research hotspots, development trends, and existing issues in the application of AI within the AF field, aiming to provide targeted recommendations for relevant researchers. Methods: Relevant publications on the application of AI in AF field were retrieved from the Web of Science Core Collection (WoSCC) database from 2013 to 2023. The bibliometric analysis was conducted by the R (4.2.2) "bibliometrix" package and VOSviewer(1.6.19). Results: Analysis of 912 publications reveals that the field of AI in AF is currently experiencing rapid development. The United States, China, and the United Kingdom have made outstanding contributions to this field. Acharya UR is a notable contributor and pioneer in the area. The following topics have been elucidated: AI's application in managing the risk of AF complications is a hot mature topic; AI-electrocardiograph for AF diagnosis and AI-assisted catheter ablation surgery are the emerging and booming topics; smart wearables for real-time AF monitoring and AI for individualized AF medication are niche and well-developed topics. Conclusion: This study offers comprehensive analysis of the origin, current status, and future trends of AI applications in AF, aiming to advance the development of the field.
Jia et al. (Tue,) conducted a other in Atrial fibrillation (n=912). Artificial intelligence was evaluated on Research hotspots, development trends, and existing issues. Artificial intelligence applications in atrial fibrillation are rapidly developing, as shown by a bibliometric analysis of 912 publications highlighting diagnosis, ablation, and risk management.
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