Artificial intelligence in cardiovascular procedures: a bibliometric and visual analysis study.

Area of Science:

• Cardiology
• Medical Informatics
• Artificial Intelligence

Background:

• Artificial intelligence (AI) integration is revolutionizing cardiovascular procedures, improving diagnostics, outcome prediction, and robotic surgeries.
• A comprehensive bibliometric analysis of AI's impact on cardiovascular interventions was previously lacking.
• This study aims to map research trends, identify key contributors, and explore emerging themes in AI-driven cardiovascular research.

Purpose of the Study:

• To conduct a bibliometric analysis of AI's impact on cardiovascular procedures.
• To examine research trends, key contributors, and emerging themes in AI-driven cardiovascular interventions.
• To provide a framework for integrating AI into clinical workflows to enhance patient care.

Main Methods:

• Publications were retrieved from the Web of Science Core Collection.
• Bibliometric analysis was performed using VOSviewer, CiteSpace, and Biblioshiny.
• Research trends, collaborations, and key themes were mapped and analyzed.

Main Results:

• AI-related cardiovascular research shows substantial growth from 1993-2024, with a significant increase from 2020-2023 (93 publications in 2023).
• The USA, China, and England are leading contributors, with Harvard University as the top institution.
• Core themes include machine learning, mortality, and cardiac surgery, with emerging trends in association, implantation, and aortic stenosis.

Conclusions:

• AI shows transformative potential in cardiovascular procedures, including diagnostic imaging, predictive modeling, and patient management.
• This bibliometric analysis underscores the increasing interest and application of AI in cardiology.
• Findings provide a framework for enhancing diagnostic accuracy, treatment strategies, and patient outcomes through AI integration.