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Global trends in coronary artery disease and artificial intelligence relevant studies: a bibliometric analysis
1Department of Vascular Surgery, The Second Hospital of Shanxi Medical University, Taiyuan, China. honglindong@sxmu.edu.cn.
Insights
This bibliometric analysis reveals a growing trend in artificial intelligence (AI) for coronary artery disease (CAD) research. Key findings highlight leading countries, institutions, and emerging research topics like AI-driven risk stratification.
Area of Science:
- Cardiology
- Medical Informatics
- Artificial Intelligence
Background:
- Coronary artery disease (CAD) is a leading global cause of mortality, impacting life expectancy and quality of life.
- Artificial intelligence (AI) offers promising advancements for accurate CAD management.
- A comprehensive bibliometric analysis of AI and CAD research trends is currently lacking.
Purpose of the Study:
- To conduct a thorough bibliometric analysis of trends and hotspots in artificial intelligence and coronary artery disease research.
- To identify key publications, influential countries, institutions, and authors in the field.
- To map the research landscape and identify emerging areas of focus.
Main Methods:
- Bibliometric analysis of 1,248 publications from 2009 to 2023.
- Data sourced from the Web of Science Core Collection (WoSCC).
- Analysis performed using CiteSpace, VOSviewer, and Excel 365.
Main Results:
- A consistent annual increase in AI and CAD publications was observed.
- The United States, China, and Germany lead in research output.
- Key research topics include AI for coronary flow reserve fraction and coronary artery calcification, with radiomics for cardiovascular risk stratification emerging as a forefront area.
Conclusions:
- This study provides the first bibliometric visualization and analysis of AI and CAD research.
- The findings offer valuable insights into current trends and research hotspots.
- This analysis serves as a reference for scholars to identify critical issues and future directions in AI and CAD research.
Objective:
Coronary artery disease (CAD) is a major global cause of death, greatly affecting life expectancy and quality of life for populations. With the advent of artificial intelligence (AI), there is new hope for accurately managing CAD. While recent studies have shown remarkable progress in AI and CAD research, there is a gap in comprehensive bibliometric analysis in this field. Therefore, this study aims to provide a thorough analysis of trends and hotspots in AI and CAD-related research utilizing bibliometrics.
Materials And Methods:
Publications on AI and CAD relevant research from 2009 to 2023 were searched through the WoS core database (WoSCC). CiteSpace, VOSviewer and Excel 365 were used to conduct the bibliometric analysis.
Results:
The bibliometric analysis included 1,248 publications, indicating a steady increase in AI and CAD-related publications annually. The United States of America (USA), China, and Germany were identified as the most influential countries in this field. Research institutions such as Cedars Sinai Med Ctr, Med Univ South Carolina, Harvard Med Sch and Capital Med Univ were the main contributors to research production. FRONT CARDIOVASC MED is the top-ranked journal, while J AM COLL CARDIOL emerged as the most cited journal. Schoepf, U. Joseph, Slomka, Piotr J., Berman, Daniel S. and Dey, Damini were the most prolific authors, while U. Rajendra Acharya was the most frequently co-cited author. Research related to the AI calculation of coronary flow reserve fraction and coronary artery calcification, based on coronary CT to identify CAD and cardiovascular risk, was a key research topic in this field. The potential link between cardiovascular risk stratification and radiomics is currently at the forefront of the field.
Conclusions:
This study is the first to use a bibliometric approach to visualize and analyze AI and CAD-related research. The findings provide insights into recent research trends and hotspots in the field and can serve as a reference for scholars to identify critical issues in this field.
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