Artificial intelligence in primary health care: A bibliometric analysis of publications from 2015 to 2024

Abstract

Objective: Primary health care (PHC) is a key approach to achieving the goal of "Health for All," and artificial intelligence (AI) can empower primary health care in various contexts, including screening, diagnosis, and treatment. Since 2019, the application of AI in primary health care has attracted increasing academic attention. This is a bibliometric study aiming to identify publication trend, distributions, frontiers, and hotspots of extant research about AI in PHC. Methods: We retrieved papers from the Web of Science Core Collection. Using VOSviewer, CiteSpace, and Bibliometrix, we conducted a bibliometric analysis to examine the publication trend, citation trend, country distribution, institution distribution, journal distribution, author distribution, reference distribution, keyword co-occurrence, and keyword burst. Results: We totally obtained 653 English-language papers published in Web of Science Core Collection from 2015 to 2024. These papers were authored by 4304 researchers in 1551 institutions from 70 countries. Both publication volume and citation frequency have increased rapidly since 2019. The USA and the United Kingdom have the most publications, citations, and collaborations in this field. The journals that publish papers on this topic are mainly from the medicine field, spanning a broader range of disciplines, including molecular biology, genetics, health, nursing, medicine, psychology, education, and the social sciences. Conclusions: This research area has attracted growing academic attention since 2019, and this trend is ongoing. Key research topics include diagnosis, family medicine, mental health, medical image analysis, and early screening of diseases.

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