Abstract
BackgroundAs a critical driving power to promote health care, the health care–related artificial intelligence (AI) literature is growing rapidly.ObjectiveThe purpose of this analysis is to provide a dynamic and longitudinal bibliometric analysis of health care–related AI publications.MethodsThe Web of Science (Clarivate PLC) was searched to retrieve all existing and highly cited AI-related health care research papers published in English up to December 2019. Based on bibliometric indicators, a search strategy was developed to screen the title for eligibility, using the abstract and full text where needed. The growth rate of publications, characteristics of research activities, publication patterns, and research hotspot tendencies were computed using the HistCite software.ResultsThe search identified 5235 hits, of which 1473 publications were included in the analyses. Publication output increased an average of 17.02% per year since 1995, but the growth rate of research papers significantly increased to 45.15% from 2014 to 2019. The major health problems studied in AI research are cancer, depression, Alzheimer disease, heart failure, and diabetes. Artificial neural networks, support vector machines, and convolutional neural networks have the highest impact on health care. Nucleosides, convolutional neural networks, and tumor markers have remained research hotspots through 2019.ConclusionsThis analysis provides a comprehensive overview of the AI-related research conducted in the field of health care, which helps researchers, policy makers, and practitioners better understand the development of health care–related AI research and possible practice implications. Future AI research should be dedicated to filling in the gaps between AI health care research and clinical applications.
Highlights
From its birth in the 1950s to present, artificial intelligence (AI) and its application in modern health care have boomed with the advancement of science and technology [1,2,3]
This analysis provides a comprehensive overview of the AI-related research conducted in the field of health care, which helps researchers, policy makers, and practitioners better understand the development of health care–related AI research and possible practice implications
According to the citation rates, artificial neural networks, support vector machines, and convolutional neural networks have the highest impact on health care
Summary
From its birth in the 1950s to present, artificial intelligence (AI) and its application in modern health care have boomed with the advancement of science and technology [1,2,3]. As a critical driving power that promotes the coming and development of industry 4.0, AI has become an indispensable component of the advancement and innovation of health care and medical diagnosis. The promise of improving diagnostic accuracy is one of AI's most exciting health care applications. AI can effectively assist health care providers in diagnosing symptoms at a faster rate than most medical professionals [8]. AI can mimic the predictive power of human doctors to improve the accuracy of diagnosis by horizontally and vertically assessing the electronic health records of patients in a short period of time [9]. As a critical driving power to promote health care, the health care–related artificial intelligence (AI) literature is growing rapidly
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