Application of artificial intelligence in rheumatic disease: a bibliometric analysis

Web of science Citation analysis
DOI: 10.1007/s10238-024-01453-6 Publication Date: 2024-08-23T19:45:31Z
ABSTRACT
The utilization of artificial intelligence (AI) in rheumatic diseases has enhanced the diagnostic accuracy diseases, enabled prediction patient outcomes, expanded treatment options, and facilitated provision individualized medical solutions. research this field been progressively growing recent years. Consequently, there is a need for bibliometric analysis to elucidate current state advancement predominant foci AI applications within diseases. Additionally, it crucial identify key contributors their interrelations field. This study aimed conduct investigate hotspots collaborative networks application disease A comprehensive search was conducted Web Science articles on published SSCI SCI-EXPANDED until January 1, 2024. Utilizing software tools like VOSviewers CiteSpace, we analyzed various parameters including publication year, journal, country, institution, authorship. extended examining cited authors, generating reference citation network graphs, creating co-citation keyword maps. trends domain were evaluated. As 2024, total 3508 have disease, exhibiting steady rise both annual frequency rate. "Scientific Reports" emerged as leading journal terms relevant publications. United States stood out country volume papers, with University California, San Francisco (UCSF) being most prolific frequently institution. Among Young Ho Lee Valentina Pedoia noted significant contributions, achieving highest average count per publication. Machine learning prominent central keyword. trend indicates interest rheumatologic its role expected become increasingly pivotal presents summary developments It offers insights into potential collaborations prospects future research, clarifying frontiers emerging directions findings serve valuable scholars studying rheumatology immunology.
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