Key result
A bibliometric analysis of 912 publications from 2013 to 2023 reveals that artificial intelligence in atrial fibrillation is rapidly developing, with AI-ECG diagnosis and complication risk management as major research hotspots.
Why the study?
AI has the potential to address existing diagnostic and therapeutic limitations in AF, but research hotspots, development trends, and existing issues needed objective investigation.
This bibliometric analysis maps the rapid growth and key research hotspots of artificial intelligence applications in atrial fibrillation from 2013 to 2023.
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.
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Jia et al. (2024) studied Atrial Fibrillation (n=912). Artificial Intelligence was evaluated on Publication trends, research hotspots, and bibliometric characteristics. A bibliometric analysis of 912 publications from 2013 to 2023 reveals that artificial intelligence in atrial fibrillation is rapidly developing, with AI-ECG diagnosis and complication risk management as major research hotspots.
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