ORIGINAL RESEARCH article

Front. Digit. Health

Sec. Health Informatics

Volume 7 - 2025 | doi: 10.3389/fdgth.2025.1608266

This article is part of the Research TopicHealthcare Text Analytics: Unlocking the Evidence from Free Text, Volume IVView all 6 articles

Research Trends in the Application of Artificial Intelligence in Nursing of Chronic disease: A Bibliometric and Network Visualization Study

Provisionally accepted
  • Northern Theater Command General Hospital, Shenyang, China

The final, formatted version of the article will be published soon.

Purpose:The incidence of chronic diseases is increasing annually and exhibits a trend of multimorbidity, posing significant challenges to global healthcare and nursing. The rapid rise of artificial intelligence has provided broad application prospects in the field of chronic disease care. However, with the increasing number of related studies, there is a lack of systematic review and prediction of future trends in this area. Bibliometric methods provide possibility for addressing this gap. This study aimed to investigate the current status, hot topics, and future prospects of artificial intelligence in the field of chronic disease care.:Literature related to artificial intelligence and chronic disease care was retrieved from the Web of Science Core Collection database, published between 2001 and 31 December 2023. Bibliometric analysis and visualization was conducted using CiteSpace 5.7.R5 and VOSviewer 1.6.19 to analyze countries/regions, institutions, journals, references, and keywords. Results :A total of 2438 articles were retrieved, indicating an explosive growth in publications over the past five years. The United States emerged as the earliest adopter of research in this domain (since 2002) and contributed the most publications (490 articles),with IEEE ACCESS being the most cited journal. Hot application areas of artificial intelligence in chronic disease care included "diabetic retinopathy," "heart disease prediction," "breast cancer," and "skin cancer." Major research methodologies encompassed "machine learning," "deep learning," "neural network," and "text mining." Potential future research hotspots include "internet of medical things."Conclusion:This study unveils the current status and development trends of artificial intelligence in chronic disease care, offering novel insights for future artificial intelligence application research.

Keywords: artificial intelligence, machine learning, Chronic Disease, Nursing, Cancer

Received: 08 Apr 2025; Accepted: 03 Jun 2025.

Copyright: © 2025 Du, Zhou and Yu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Yuexin Yu, Northern Theater Command General Hospital, Shenyang, China

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