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Systematic Review on Artificial Intelligence in Rheumatology Practice: From Implementation Concerns to Imaging and
Raffaele Barile1, Cinzia Rotondo1, Giulio Giancaspro1
1Department of Medical and Surgical Sciences, University of Foggia, Foggia, Apulia, Italy.
International Journal of Rheumatic Diseases
|August 4, 2026
Summary
Artificial intelligence (AI) shows great potential in rheumatology, improving diagnostics and monitoring with high accuracy. Further research is needed to overcome challenges for successful clinical integration of AI tools.
Area of Science:
- Rheumatology
- Artificial Intelligence
- Medical Informatics
Background:
- Artificial intelligence (AI) integration in healthcare offers solutions for complex rheumatology challenges.
- This review explores current AI applications within rheumatological practice.
Purpose of the Study:
- Systematically evaluate AI applications in rheumatology.
- Assess the clinical performance of AI tools.
- Identify future research directions for AI in rheumatology.
Main Methods:
- Comprehensive literature review of AI in rheumatology.
- Focus on diagnostic imaging, clinical decision support, and disease monitoring.
- Analysis across major rheumatic conditions.
Main Results:
- AI shows promising performance in rheumatology, exceeding 80%-90% accuracy for imaging and classification.
- AI applications include automated radiographic scoring and real-time disease monitoring.
- AI tools are being developed for various rheumatic conditions.
Conclusions:
- AI holds significant potential for rheumatology practice.
- Clinical implementation requires addressing data quality, algorithm transparency, and integration challenges.
- Further development is needed to fully realize AI's benefits in rheumatology.