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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.
Background:
The integration of artificial intelligence (AI) into healthcare has shown significant promise in addressing complex diagnostic and therapeutic challenges in rheumatology. This review examines the current state of AI applications across rheumatological practice.
Objective:
To systematically evaluate AI applications in rheumatology, assess their clinical performance and identify future research directions.
Methods:
We conducted a comprehensive literature review of AI applications in rheumatology, focusing on diagnostic imaging, clinical decision support and disease monitoring across major rheumatic conditions.
Results:
AI demonstrates promising performance across multiple domains, with diagnostic accuracies frequently exceeding 80%-90% for imaging interpretation and disease classification. Applications span from automated radiographic scoring to real-time disease monitoring.
Conclusions:
While AI shows significant potential in rheumatology, successful clinical implementation requires addressing challenges related to data quality, algorithm transparency and clinical integration.