Evidence map›Paper›PMID 40517271›Full record

ArticleJournal of health, population, and nutrition2025

Areas of research focus and trends in the research on the application of AIGC in healthcare.

Chen Wang, Yingying Zhu, Xuejiao Zhang, Xueqing Chen, Yilin Li, Yongjie Tan, Huiying Qi

Abstract read
In one paragraph

Article in Journal of health, population, and nutrition, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Chen WangDepartment of Health Informatics and Management, School of Health Humanities, Peking University, Beijing, 100191, China.
Yingying ZhuSchool of Nursing, Peking University, Beijing, 100191, China.
Xuejiao ZhangSchool of Nursing, Peking University, Beijing, 100191, China.
Xueqing ChenSchool of Nursing, Peking University, Beijing, 100191, China.
Yilin LiSchool of Basic Medical Sciences, Capital Medical University, Beijing, 100069, China.
Yongjie TanSchool of Basic Medical Sciences, Peking University, Beijing, 100191, China.
Huiying QiDepartment of Health Informatics and Management, School of Health Humanities, Peking University, Beijing, 100191, China. qhy@bjmu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAs a crucial part of current AI technology, the extent of AIGC's (Artificial Intelligence Generated Content) impact on healthcare, its potential to further drive the development of intelligent healthcare, and its ability to alleviate the current scarcity of medical resources have become highly discussed topics in academia and the healthcare sector. Our aim is to conduct bibliometric study to analyze and visualize the current research hotspots and trends related to the application of AIGC in healthcare.

methodsStudies related to the application of AIGC in healthcare that were published from November 30 2022, to December 31 2023, were retrieved via the Web of Science Core Collection. CiteSpace and Microsoft Excel were utilized to analyze and visualize the annual publications, countries, institutions, authors, journals, high cited literature and keywords.

resultsA total of 3411papers were included, and the number of publications is increasing rapidly in recent two years. The United States and Harvard University are respectively the leading country and institution in terms of the number of research publications on the application of AIGC in healthcare. Thongprayoon Charat and Cheungpasitporn Wisit are outstanding investigators in this field. Nature is the most influential journal in the field of AIGC' s application in healthcare, whereas Cureus Journal of Medical Science boasts the highest number of publications on this topic. The analysis of keywords and high cited literature has identified current research hotspots, including the impact exploration of the application of AIGC in the healthcare industry, the assessment of applicability, the perception of healthcare related personnel, and the development of AIGC in the healthcare field.

conclusionsThis paper presents a bibliometric analysis of the research framework and hotspots concerning the application of AIGC in healthcare. The analysis aims to provide a comprehensive understanding of this field for researchers. Future research should focus on establishing regulatory mechanism, optimizing healthcare information services, clarifying the role of AIGC, and continuously developing medical large language models.

Indexed as

Artificial IntelligenceBibliometricsBiomedical ResearchDelivery of Health CareHumansAIGCBibliometricChatGPTDevelopment trendsHealthcareResearch focuses

Identifiers

PMID40517271
PMCPMC12166634

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.