Department of Vascular Surgery, The Second Hospital of Shanxi Medical University, Taiyuan, China.
Eur Rev Med Pharmacol Sci. 2024 Jan;28(1):1-22. doi: 10.26355/eurrev_202401_34886.
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.
目的：冠心病（CAD）是全球主要的死亡原因，极大地影响了人群的预期寿命和生活质量。随着人工智能（AI）的出现，对 CAD 进行准确管理有了新的希望。虽然最近的研究表明 AI 和 CAD 研究取得了显著进展，但在该领域的综合文献计量分析方面存在差距。因此，本研究旨在利用文献计量学对 AI 和 CAD 相关研究的趋势和热点进行全面分析。
材料和方法：通过 WoS 核心数据库（WoSCC）搜索 2009 年至 2023 年与 AI 和 CAD 相关的研究出版物。使用 CiteSpace、VOSviewer 和 Excel 365 进行文献计量分析。
结果：文献计量分析共纳入 1248 篇出版物，表明与 AI 和 CAD 相关的出版物数量逐年稳步增加。美国、中国和德国被确定为该领域最具影响力的国家。Cedars Sinai Med Ctr、Med Univ South Carolina、Harvard Med Sch 和 Capital Med Univ 等研究机构是研究成果的主要贡献者。FRONT CARDIOVASC MED 是排名最高的期刊，而 J AM COLL CARDIOL 则是被引频次最高的期刊。Schoepf, U. Joseph、Slomka、Piotr J.、Berman、Daniel S. 和 Dey、Damini 是最具影响力的作者，而 U. Rajendra Acharya 是被引频次最高的作者。基于冠状动脉 CT 识别 CAD 和心血管风险，对冠状动脉血流储备分数和冠状动脉钙化的 AI 计算、心血管风险分层与放射组学之间的潜在联系等方面的研究是该领域的关键研究课题。
结论：本研究首次使用文献计量学方法对 AI 和 CAD 相关研究进行可视化和分析。研究结果提供了对该领域最新研究趋势和热点的深入了解，可为学者提供参考，帮助他们确定该领域的关键问题。
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