Dalky Alaa, Altawalbih Mahmoud, Alshanik Farah, Khasawneh Rawand A, Tawalbeh Rawan, Al-Dekah Arwa M, Alrawashdeh Ahmad, Quran Tamara O, ALBashtawy Mohammed
Department of Health Management and Policy, Faculty of Medicine, Jordan University of Science and Technology, Irbid 22110, Jordan.
Department of Allied Medical Sciences, Faculty of Applied Medical Sciences, Jordan University of Science and Technology, Irbid 22110, Jordan.
Healthcare (Basel). 2025 Apr 13;13(8):892. doi: 10.3390/healthcare13080892.
: The increasing application of artificial intelligence (AI) and machine learning (ML) in health and medicine has attracted a great deal of research interest in recent decades. This study aims to provide a global and historical picture of research concerning AI and ML in health and medicine. : We used the Scopus database for searching and extracted articles published between 2000 and 2024. Then, we generated information about productivity, citations, collaboration, most impactful research topics, emerging research topics, and author keywords using Microsoft Excel 365 and VOSviewer software (version 1.6.20). : We retrieved a total of 22,113 research articles, with a notable surge in research activity in recent years. Core journals were and , and core institutions included Harvard Medical School and the Ministry of Education of the People's Republic of China, while core countries comprised the United States, China, India, the United Kingdom, and Saudi Arabia. Citation trends indicated substantial growth and recognition of AI's and ML impact on health and medicine. Frequent author keywords identified key research hotspots, including specific diseases like Alzheimer's disease, Parkinson's diseases, COVID-19, and diabetes. The author keyword analysis identified "deep learning", "convolutional neural network", and "classification" as dominant research themes. : AI's transformative potential in AI and ML in health and medicine holds promise for improving global health outcomes.
近几十年来，人工智能（AI）和机器学习（ML）在健康与医学领域的应用日益广泛，引发了大量研究兴趣。本研究旨在呈现健康与医学领域中关于人工智能和机器学习研究的全球及历史概况。我们使用Scopus数据库进行检索，并提取了2000年至2024年发表的文章。然后，我们使用Microsoft Excel 365和VOSviewer软件（版本1.6.20）生成了有关生产力、引用情况、合作、最具影响力的研究主题、新兴研究主题以及作者关键词的信息。我们共检索到22,113篇研究文章，近年来研究活动显著激增。核心期刊有《》和《》，核心机构包括哈佛医学院和中华人民共和国教育部，而核心国家包括美国、中国、印度、英国和沙特阿拉伯。引用趋势表明人工智能和机器学习对健康与医学的影响得到了显著增长和认可。频繁出现的作者关键词确定了关键研究热点，包括阿尔茨海默病、帕金森病、COVID - 19和糖尿病等特定疾病。作者关键词分析确定“深度学习”“卷积神经网络”和“分类”为主要研究主题。人工智能和机器学习在健康与医学领域的变革潜力有望改善全球健康状况。
