Application of artificial intelligence in rheumatic disease: a bibliometric analysis

Aug 22, 2024Clinical and experimental medicine

Use of artificial intelligence in rheumatic diseases: a publication analysis

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Abstract

As of January 1, 2024, a total of 3508 articles have been published on the application of artificial intelligence (AI) in rheumatic disease.

There has been a steady rise in both the annual publication frequency and rate of articles related to AI in rheumatic diseases.
The journal 'Scientific Reports' is identified as the leading publication outlet for this research.
The United States is the predominant country for published papers in this field.
The University of California, San Francisco (UCSF) is noted as the most prolific and frequently cited institution.
Machine learning is highlighted as a prominent and central keyword in the literature.
The analysis indicates a growing interest in AI applications within rheumatologic diseases, suggesting its role may become increasingly pivotal.

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

Key numbers

3508

Total Publications

Total articles published on AI applications in rheumatic diseases by January 1, 2024.

781

USA Publications

Number of articles published by the United States in this field.

465

Machine Learning Occurrences

Frequency of the keyword 'machine learning' in the analyzed literature.

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Application of artificial intelligence in rheumatic disease: a bibliometric analysis

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