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

Author:

Hussain Walayat1,Mabrok Mohamed2,Gao Honghao3,Rabhi Fethi A.4,Rashed Essam A.5ORCID

Affiliation:

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

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

3. School of Computer Engineering and Science, Shanghai University, Shanghai, China

4. School of Computer Science and Engineering, University of New South Wales (UNSW), Sydney, Australia

5. Graduate School of Information Science, University of Hyogo, Kobe, Japan

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’.

Funder

Australian Catholic University

Qatar Japan Research Collaboration

Publisher

SAGE Publications

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