Artículo

Artificial intelligence and atrial fibrillation: A bibliometric analysis from 2013 to 2023

Resumen

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.
Jrade, Ahmad (12804778900); Jalaei, Farnaz (57212026747); Zhang, Jieying Jane (59228484300); Jalilzadeh Eirdmousa, Saeed (59228444800); Jalaei, Farzad (54894358100)
Potential Integration of Bridge Information Modeling and Life Cycle Assessment/Life Cycle Costing Tools for Infrastructure Projects within Construction 4.0: A Review
2023
10.3390/su152015049
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85199226134&doi=10.3390%2fsu152015049&partnerID=40&md5=b503d960a132c3df787b4cb99ad749dc
Department of Civil Engineering, University of Ottawa, Ottawa, K1N 6N5, ON, Canada; National Research Council Canada, Government of Canada, Ottawa, K1A 0R6, ON, Canada
All Open Access; Gold Open Access
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