Artificial intelligence in rheumatoid arthritis research: A bibliometric analysis from 2004 to 2023

被引:0
作者
Liu, Yang [1 ]
Su, Yazhen [1 ]
Wu, Zewen [1 ]
Gao, Jinfang [1 ]
Gong, Xueyan [1 ]
Zhang, Liyun [1 ]
机构
[1] Shanxi Med Univ, Shanxi Bethune Hosp, Tongji Shanxi Hosp, Hosp 3,Shanxi Acad Med Sci,Dept Rheumatol, Taiyuan 030032, Shanxi, Peoples R China
来源
RHEUMATOLOGY & AUTOIMMUNITY | 2024年 / 4卷 / 03期
关键词
artificial intelligence; bibliometric analysis; big data; rheumatoid arthritis; VOSviewer; EULAR RECOMMENDATIONS; MEDICAL ULTRASOUND; DISEASE; QUANTIFICATION; CLASSIFICATION; SEGMENTATION; ASSOCIATION; MANAGEMENT; EROSIONS; CRITERIA;
D O I
10.1002/rai2.12142
中图分类号
R392 [医学免疫学]; Q939.91 [免疫学];
学科分类号
100102 ;
摘要
Background: Artificial intelligence (AI) holds promise for the screening, diagnosis, and management of patients with rheumatoid arthritis (RA). This study explores the current status of AI in RA from 2004 to 2023 using bibliometric analysis and outlines prospective research trends and directions. Methods: The Web of Science Core Collection database was searched for studies related to AI in patients with RA between 2004 and 2023. VOS viewer was used for bibliometric analysis. Results: A total of 601 articles from 65 countries, primarily the United States of America, China, and the United Kingdom, were included. The research revealed that the number of global studies on AI in RA surged in 2019, with the United States of America and China producing the highest numbers of articles. Brigham and Women's Hospital emerged as the leading research institution, whereas Frontiers in Immunology was the journal with the most articles on this topic. Keywords such as " rheumatoid arthritis," " " machine learning," " " artificial intelligence," " and " inflammation" were frequently used to indicate their significance in the field. Conclusions: The synergy of AI and big data can enhance screening, early diagnosis, therapeutic decision-making, and ground-up drug discovery for patients with RA. AI technology can assist rheumatologists more effectively in diagnosing and predicting personalized and efficacious therapeutic drugs early in disease progression and providing continuous monitoring.
引用
收藏
页码:133 / 144
页数:12
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