Review of 2024 publications on the applications of artificial intelligence in rheumatology

The integration of artificial intelligence (AI) into rheumatology has revolutionized research and clinical practice, offering transformative advancements in diagnostics, biomarker discovery, genomics, digital health technologies, and personalized medicine. This review provides a comprehensive analysis of cutting-edge AI applications in rheumatology, highlighting deep learning models for imaging diagnostics, AI-powered genomic analysis, and wearable health technologies for continuous disease monitoring. The findings demonstrate that AI enhances diagnostic precision, facilitates early disease detection, and enables personalized therapeutic strategies. However, significant challenges remain, including limited clinician adoption, ethical concerns, data privacy issues, and the need for robust model validation. A recent survey revealed that 73% of rheumatologists have never used AI in clinical practice, emphasizing the urgent need for targeted training and interdisciplinary collaboration. Additionally, AI is reshaping rheumatology research by optimizing drug discovery, clinical trial designs, and predictive analytics. Overcoming current barriers requires a multidisciplinary approach involving rheumatologists, AI specialists, and regulatory bodies to ensure the ethical, scalable, and effective implementation of AI-driven solutions in rheumatology.