Zhang Yalan, Xie Jingwen, Fu Enlong, Cai Wan, Xu Wentan
Department of Pharmacy, The Second Affiliated Hospital of Fujian Medical University Quanzhou, Fujian, China.
Guangzhou University of Chinese Medicine Guangzhou, Guangdong, China.
Am J Transl Res. 2024 Mar 15;16(3):1029-1035. doi: 10.62347/HSFE6936. eCollection 2024.
To perform a comprehensive bibliometric analysis of global publications on the applications of artificial intelligence (AI) in cardiology.
Documents related to AI in cardiology published between 2002 and 2022 were retrieved from Web of Science Core Collection. R package "bibliometrix", VOSviewers and Microsoft Excel were applied to perform the bibliometric analysis.
A total of 4332 articles were included. United States topped the list of countries publishing articles, followed by China and United Kingdom. The Harvard University was the institution that contributed the most to this field, followed by University of California System and University of London. Disease risk prediction, diagnosis, treatment, disease detection, and prognosis assessment were the research hotspots for AI in cardiology.
Enhancing cooperation between different countries and institutions is a critical step in leading to breakthroughs in the application of AI in cardiology. It is foreseeable that the application of machine learning and deep learning in various areas of cardiology will be a research priority in the coming years.
对全球人工智能（AI）在心脏病学应用方面的出版物进行全面的文献计量分析。
从Web of Science核心合集中检索2002年至2022年期间发表的与AI在心脏病学中应用相关的文献。应用R包“bibliometrix”、VOSviewer和Microsoft Excel进行文献计量分析。
共纳入4332篇文章。美国在发表文章的国家中位居榜首，其次是中国和英国。哈佛大学是该领域贡献最大的机构，其次是加利福尼亚大学系统和伦敦大学。疾病风险预测、诊断、治疗、疾病检测和预后评估是AI在心脏病学中的研究热点。
加强不同国家和机构之间的合作是在AI在心脏病学应用方面取得突破的关键一步。可以预见，机器学习和深度学习在心脏病学各个领域的应用将是未来几年的研究重点。
