A Bibliometric Analysis and Visualization of Medical Artificial Intelligence Research

Abstract

In recent years, there has been an impressive increase in the use of artificial intelligence (AI) in medical treatment. Studies have explored many topics in the field of medical AI; however, few of them have systematically reviewed the overall area. This chapter retrieves 532 papers on medical AI from Social Sciences Citation Index core database of the Web of Science from 2013 to 2022. Two bibliometric and network analysis tools, including CiteSpace and HistCite, are used to identify the time-and-space knowledge map, research hotspots, emerging trends and key studies of medical AI research. A co-word network of medical AI is constructed to reveal that the field focuses more on the topic of machine learning. The analysis of the burst literature on medical AI indicates the research trends in the sub-sections such as law and ethics. Furthermore, the analysis of the co-citation uncovers the key studies in the field of medical AI. The results of bibliometric analysis illustrate the current situation, past evolution, and future trends in medical AI research, and identify hotspots and future research directions.

Citation

Liu, Y. and Mu, Y. (2024), "A Bibliometric Analysis and Visualization of Medical Artificial Intelligence Research", Singh Kaurav, R.P. and Mishra, V. (Ed.) Review of Technologies and Disruptive Business Strategies (Review of Management Literature, Vol. 3), Emerald Publishing Limited, Leeds, pp. 83-96. https://doi.org/10.1108/S2754-586520240000003005