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Abstract：
The development of artificial intelligence (AI) has revolutionised the medical system, empowering healthcare professionals to analyse complex nonlinear big data and identify hidden patterns, facilitating well-informed decisions. Over the last decade, there has been a notable trend of research in AI, machine learning (ML), and their associated algorithms in health and medical systems. These approaches have transformed the healthcare system, enhancing efficiency, accuracy, personalised treatment, and decision-making. Recognising the importance and growing trend of research in the topic area, this paper presents a bibliometric analysis of AI in health and medical systems. The paper utilises the Web of Science (WoS) Core Collection database, considering documents published in the topic area for the last four decades. A total of 64,063 papers were identified from 1983 to 2022. The paper evaluates the bibliometric data from various perspectives, such as annual papers published, annual citations, highly cited papers, and most productive institutions, and countries. The paper visualises the relationship among various scientific actors by presenting bibliographic coupling and co-occurrences of the author\'s keywords. The analysis indicates that the field began its significant growth in the late 1970s and early 1980s, with significant growth since 2019. The most influential institutions are in the USA and China. The study also reveals that the scientific community\'s top keywords include \'ML\', \'Deep Learning\', and \'Artificial Intelligence\'.
摘要：
人工智能（AI）的发展彻底改变了医疗系统，使医疗保健专业人员能够分析复杂的非线性大数据并识别隐藏的模式，促进明智的决策。在过去的十年里，人工智能的研究有一个显著的趋势，机器学习(ML)以及它们在健康和医疗系统中的相关算法。这些方法改变了医疗保健系统，提高效率,准确度,个性化治疗,和决策。认识到主题领域研究的重要性和发展趋势，本文对健康和医疗系统中的人工智能进行了文献计量分析。本文利用了WebofScience(WoS)核心收藏数据库，考虑过去四十年在主题领域发表的文件。从1983年到2022年，共确认了64,063篇论文。本文从不同角度对文献计量数据进行了评价，例如发表的年度论文，年度引文，被高度引用的论文，和大多数生产性机构，和国家。本文通过呈现作者关键词的书目耦合和共同出现，将各种科学行为者之间的关系可视化。分析表明，该领域在1970年代末和1980年代初开始了显着的增长，2019年以来大幅增长。最有影响力的机构在美国和中国。该研究还表明，科学界的热门关键词包括“ML”，\'深度学习\',和“人工智能”。
