Artificial intelligence applied in cardiovascular disease: a bibliometric and visual analysis.

Area of Science:

• Cardiology
• Medical Informatics
• Artificial Intelligence

Background:

• Artificial intelligence (AI) is increasingly utilized in diagnosing and predicting outcomes for various diseases, including cardiovascular conditions.
• AI demonstrates significant potential for rapid and accurate disease diagnosis.

Purpose of the Study:

• To conduct a bibliometric analysis of research applying AI in the field of cardiovascular disease.
• To identify current research trends and explore future research hotspots in AI for cardiovascular disease.

Main Methods:

• Bibliometric analysis of articles and reviews published between 2000 and 2023 from the Web of Science Core Collection.
• Utilized Microsoft Excel for data analysis and VOSviewer, Citespace, and an online platform for co-authorship, co-citation, and keyword co-occurrence analysis.

Main Results:

• A total of 4,611 publications were analyzed, showing exponential growth in AI research for cardiovascular disease.
• The USA was the most productive country, and key institutions/authors were identified, though inter-institutional cooperation was limited.
• Core keywords included 'classification', 'diagnosis', and 'risk', with 'late gadolinium enhancement' and 'carotid ultrasound' as emerging research hotspots.

Conclusions:

• AI holds substantial promise for applications in cardiovascular disease.
• Cardiovascular imaging techniques and algorithm selection are key research areas with predicted future growth.