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用人工智能变革医疗保健:对卫生系统40年进展的文献计量分析

Revolutionising healthcare with artificial intelligence: A bibliometric analysis of 40 years of progress in health systems.

作者信息

Hussain Walayat, Mabrok Mohamed, Gao Honghao, Rabhi Fethi A, Rashed Essam A

机构信息

Peter Faber Business School, Australian Catholic University, North Sydney, Australia.

Department of Mathematics and Statistics, Qatar University, Doha, Qatar.

出版信息

Digit Health. 2024 May 28;10:20552076241258757. doi: 10.1177/20552076241258757. eCollection 2024 Jan-Dec.

DOI:10.1177/20552076241258757
PMID:38817839
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11138196/
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模式,从而促进明智的决策。在过去十年中,人工智能、机器学习(ML)及其在健康和医疗系统中的相关算法的研究呈现出显著趋势。这些方法改变了医疗保健系统,提高了效率、准确性、个性化治疗水平和决策能力。认识到该主题领域研究的重要性和不断增长的趋势,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。本文利用科学网(WoS)核心合集数据库,考虑了过去四十年在该主题领域发表的文献。从1983年到2022年共识别出64,063篇论文。本文从多个角度评估文献计量数据,如年度发表论文数、年度被引次数、高被引论文以及最多产的机构和国家。本文通过展示作者关键词的文献耦合和共现情况,直观呈现了不同科学参与者之间的关系。分析表明,该领域在20世纪70年代末和80年代初开始显著增长,自2019年以来增长显著。最具影响力的机构位于美国和中国。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”。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc25/11138196/1afade1f040e/10.1177_20552076241258757-fig6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc25/11138196/ca8ff7a10819/10.1177_20552076241258757-fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc25/11138196/670cfb2f3925/10.1177_20552076241258757-fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc25/11138196/2637ecaaee8c/10.1177_20552076241258757-fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc25/11138196/b55238282b42/10.1177_20552076241258757-fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc25/11138196/a22fcb43ea79/10.1177_20552076241258757-fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc25/11138196/1afade1f040e/10.1177_20552076241258757-fig6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc25/11138196/ca8ff7a10819/10.1177_20552076241258757-fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc25/11138196/670cfb2f3925/10.1177_20552076241258757-fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc25/11138196/2637ecaaee8c/10.1177_20552076241258757-fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc25/11138196/b55238282b42/10.1177_20552076241258757-fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc25/11138196/a22fcb43ea79/10.1177_20552076241258757-fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc25/11138196/1afade1f040e/10.1177_20552076241258757-fig6.jpg

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