Evolution of artificial intelligence in healthcare: a 30-year bibliometric study
IntroductionIn recent years, the development of artificial intelligence (AI) technologies, including machine learning, deep learning, and large language models, has significantly supported clinical work. Concurrently, the integration of artificial intelligence with the medical field has garnered inc...
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Frontiers Media S.A.
2025-01-01
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| Series: | Frontiers in Medicine |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fmed.2024.1505692/full |
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| author | Yaojue Xie Yuansheng Zhai Yuansheng Zhai Guihua Lu Guihua Lu |
| author_facet | Yaojue Xie Yuansheng Zhai Yuansheng Zhai Guihua Lu Guihua Lu |
| author_sort | Yaojue Xie |
| collection | DOAJ |
| description | IntroductionIn recent years, the development of artificial intelligence (AI) technologies, including machine learning, deep learning, and large language models, has significantly supported clinical work. Concurrently, the integration of artificial intelligence with the medical field has garnered increasing attention from medical experts. This study undertakes a dynamic and longitudinal bibliometric analysis of AI publications within the healthcare sector over the past three decades to investigate the current status and trends of the fusion between medicine and artificial intelligence.MethodsFollowing a search on the Web of Science, researchers retrieved all reviews and original articles concerning artificial intelligence in healthcare published between January 1993 and December 2023. The analysis employed Bibliometrix, Biblioshiny, and Microsoft Excel, incorporating the bibliometrix R package for data mining and analysis, and visualized the observed trends in bibliometrics.ResultsA total of 22,950 documents were collected in this study. From 1993 to 2023, there was a discernible upward trajectory in scientific output within bibliometrics. The United States and China emerged as primary contributors to medical artificial intelligence research, with Harvard University leading in publication volume among institutions. Notably, the rapid expansion of emerging topics such as COVID-19 and new drug discovery in recent years is noteworthy. Furthermore, the top five most cited papers in 2023 were all pertinent to the theme of ChatGPT.ConclusionThis study reveals a sustained explosive growth trend in AI technologies within the healthcare sector in recent years, with increasingly profound applications in medicine. Additionally, medical artificial intelligence research is dynamically evolving with the advent of new technologies. Moving forward, concerted efforts to bolster international collaboration and enhance comprehension and utilization of AI technologies are imperative for fostering novel innovations in healthcare. |
| format | Article |
| id | doaj-art-e31a12edcb72413c89461ed17102c51d |
| institution | Kabale University |
| issn | 2296-858X |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Medicine |
| spelling | doaj-art-e31a12edcb72413c89461ed17102c51d2025-02-07T10:49:02ZengFrontiers Media S.A.Frontiers in Medicine2296-858X2025-01-011110.3389/fmed.2024.15056921505692Evolution of artificial intelligence in healthcare: a 30-year bibliometric studyYaojue Xie0Yuansheng Zhai1Yuansheng Zhai2Guihua Lu3Guihua Lu4Yangjiang Bainian Yanshen Medical Technology Co., Ltd., Yangjiang, ChinaDepartment of Cardiology, Heart Center, First Affiliated Hospital, Sun Yat-sen University, Guangzhou, ChinaNHC Key Laboratory of Assisted Circulation (Sun Yat-sen University), Guangzhou, ChinaDepartment of Cardiology, Heart Center, First Affiliated Hospital, Sun Yat-sen University, Guangzhou, ChinaNHC Key Laboratory of Assisted Circulation (Sun Yat-sen University), Guangzhou, ChinaIntroductionIn recent years, the development of artificial intelligence (AI) technologies, including machine learning, deep learning, and large language models, has significantly supported clinical work. Concurrently, the integration of artificial intelligence with the medical field has garnered increasing attention from medical experts. This study undertakes a dynamic and longitudinal bibliometric analysis of AI publications within the healthcare sector over the past three decades to investigate the current status and trends of the fusion between medicine and artificial intelligence.MethodsFollowing a search on the Web of Science, researchers retrieved all reviews and original articles concerning artificial intelligence in healthcare published between January 1993 and December 2023. The analysis employed Bibliometrix, Biblioshiny, and Microsoft Excel, incorporating the bibliometrix R package for data mining and analysis, and visualized the observed trends in bibliometrics.ResultsA total of 22,950 documents were collected in this study. From 1993 to 2023, there was a discernible upward trajectory in scientific output within bibliometrics. The United States and China emerged as primary contributors to medical artificial intelligence research, with Harvard University leading in publication volume among institutions. Notably, the rapid expansion of emerging topics such as COVID-19 and new drug discovery in recent years is noteworthy. Furthermore, the top five most cited papers in 2023 were all pertinent to the theme of ChatGPT.ConclusionThis study reveals a sustained explosive growth trend in AI technologies within the healthcare sector in recent years, with increasingly profound applications in medicine. Additionally, medical artificial intelligence research is dynamically evolving with the advent of new technologies. Moving forward, concerted efforts to bolster international collaboration and enhance comprehension and utilization of AI technologies are imperative for fostering novel innovations in healthcare.https://www.frontiersin.org/articles/10.3389/fmed.2024.1505692/fullartificial intelligencehealth caremedicineChatGPTbibliometric study |
| spellingShingle | Yaojue Xie Yuansheng Zhai Yuansheng Zhai Guihua Lu Guihua Lu Evolution of artificial intelligence in healthcare: a 30-year bibliometric study Frontiers in Medicine artificial intelligence health care medicine ChatGPT bibliometric study |
| title | Evolution of artificial intelligence in healthcare: a 30-year bibliometric study |
| title_full | Evolution of artificial intelligence in healthcare: a 30-year bibliometric study |
| title_fullStr | Evolution of artificial intelligence in healthcare: a 30-year bibliometric study |
| title_full_unstemmed | Evolution of artificial intelligence in healthcare: a 30-year bibliometric study |
| title_short | Evolution of artificial intelligence in healthcare: a 30-year bibliometric study |
| title_sort | evolution of artificial intelligence in healthcare a 30 year bibliometric study |
| topic | artificial intelligence health care medicine ChatGPT bibliometric study |
| url | https://www.frontiersin.org/articles/10.3389/fmed.2024.1505692/full |
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