Artificial intelligence in rheumatology: current achievements, prospects, and сhallenges

Kovalenko V.M.¹, Yatsyshyn R.I.², Bilyavska Yu.V.¹, Doskaliuk B.V.²

• ¹State University «National Scientific Center «Institute of Cardiology, Clinical and Regenerative Medicine named after Academician M.D.Strazheska» National Academy of Sciences of Ukraine
• ²Ivano-Frankivsk National Medical University

Summary. Artificial intelligence (AI) is rapidly advancing, opening new opportunities to improve diagnosis, outcome prediction, and personalized treatment for patients with rheumatological diseases. This literature review highlights key advancements in the application of machine learning and deep learning for diagnostics, patient stratification, and the development of individualized therapeutic algorithms. Special attention is given to progress in analyzing molecular subtypes of systemic sclerosis, identifying immunological patterns in juvenile idiopathic arthritis, and developing models for predicting therapeutic responses in rheumatoid arthritis. The review also explores key challenges in the implementation of AI in rheumatology, including issues of data quality, algorithm transparency, ethical considerations, and infrastructure limitations. Despite these obstacles, the use of AI has significant potential to revolutionize rheumatological practice by enabling the analysis of large datasets and support clinical decision-making. The article emphasizes the importance of interdisciplinary collaboration to overcome existing barriers and ensure equitable access to these innovative technologies. This review summarizes the current state of research and outlines future prospects for application of AI in rheumatology, aiming to enhance the quality of medical care, personalize treatments, and optimize outcomes for patients.