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. 2024 Sep 3;11(3):100182.
doi: 10.1016/j.fhj.2024.100182. eCollection 2024 Sep.

Bibliometric analysis of artificial intelligence in healthcare research: Trends and future directions

Renganathan Senthil  1 , Thirunavukarasou Anand  2   3 , Chaitanya Sree Somala  3 , Konda Mani Saravanan  3   4
Affiliations

Bibliometric analysis of artificial intelligence in healthcare research: Trends and future directions

Renganathan Senthil et al. Future Healthc J. .

Abstract

Objective: The presence of artificial intelligence (AI) in healthcare is a powerful and game-changing force that is completely transforming the industry as a whole. Using sophisticated algorithms and data analytics, AI has unparalleled prospects for improving patient care, streamlining operational efficiency, and fostering innovation across the healthcare ecosystem. This study conducts a comprehensive bibliometric analysis of research on AI in healthcare, utilising the SCOPUS database as the primary data source.

Methods: Preliminary findings from 2013 identified 153 publications on AI and healthcare. Between 2019 and 2023, the number of publications increased exponentially, indicating significant growth and development in the field. The analysis employs various bibliometric indicators to assess research production performance, science mapping techniques, and thematic mapping analysis.

Results: The study reveals insights into research hotspots, thematic focus, and emerging trends in AI and healthcare research. Based on an extensive examination of the Scopus database provides a brief overview and suggests potential avenues for further investigation.

Conclusion: This article provides valuable contributions to understanding the current landscape of AI in healthcare, offering insights for future research directions and informing strategic decision making in the field.

Keywords: Artificial intelligence; Bibliometric analysis; COVID-19; Emerging trends; Scientific production.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Fig. 1
Fig. 1
Systematic search of documents in Scopus database using the keyword ‘Artificial intelligence AND healthcare’.
Fig. 2
Fig. 2
Annual scientific production of articles dealing with AI in healthcare in the Scopus database.
Fig. 3
Fig. 3
Authors scientific production dealing AI in healthcare in Scopus database.
Fig. 4
Fig. 4
The most productive countries dealing with AI in healthcare are in the Scopus database.
Fig. 5
Fig. 5
Most productive affiliations dealing with AI in healthcare are in the Scopus database.
Fig. 6
Fig. 6
The annual source distribution deals with AI in healthcare in the Scopus database.
Fig. 7
Fig. 7
The most frequently occurring keywords in documents related to AI and healthcare from 2013 to 2023.
Fig. 8
Fig. 8
Keyword co-occurrence network of the documents related to artificial intelligence and healthcare.
Fig. 9
Fig. 9
Thematic mapping of the keywords on the documents related to AI in healthcare concepts.
See this image and copyright information in PMC

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