Previously submitted to: Journal of Medical Internet Research (no longer under consideration since Jan 08, 2024)
Date Submitted: May 11, 2023
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Research Trends of Medical Big Data: A Bibliometric Analysis
ABSTRACT
Background:
Medical big data has gained widespread attention worldwide and has been cross-applied in a number of fields including computing, medicine and engineering.
Objective:
To summarize the current trend of research and inform the direction of future research in medical big data through bibliometric and visualized analysis.
Methods:
We comprehensively searched all relevant papers in the core database of Web of Science. Vosviewer(version 1.6.18.0), R (version 4.2.1) and Scimago Graphic were used to systematically summerized the main authors, journals, countries and organizations in the field, and keywords were also analyzed.
Results:
996 papers were included in the analysis, the most of which were article with the number of 711. Among them, the United States has an outstanding advantage in number of published articles, journals, and relevant institutions. We also analyzed the authoritative journals and authoritative authors in the field based on the number of paper published and cited. Besides, through cluster analysis, we extracted research keywords in the field by time and hotness, including system, medicine, patient, etc. However, medical big data faces problems of data silos and uneven development at the national level. By taking advantages of multiple disciplines, putting medical big data into clinical practice and enabling precision medicine may be the focus of future development.
Conclusions:
Medical big data has been a hot spot in recent years. In the future, precision medicine and intelligent medicine will become the research focus of medical big data.
Citation
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