Artificial Intelligence in the Diagnosis and Treatment of Rheumatoid Arthritis: Current Status and Future Prospects

Rheumatoid arthritis (RA) is a prevalent autoimmune disease with unknown causes, characterized by joint damage and chronic polyarthritis. The exact pathogenesis of RA remains unclear, leading to a need for advanced approaches. Artificial intelligence (AI), specifically machine learning and deep learning, has gained traction in healthcare and medicine. AI algorithms have shown promise in RA diagnosis, prognosis, treatment monitoring, drug discovery, and basic science research support. In addition to conventional treatments, alternative medicine, including traditional Indian, Korean, and Chinese herbs, is being explored for RA management. The integration of AI into real-world scenarios is a significant step forward, with the potential for the development of effective and novel RA treatments. Many studies showed that AI algorithms have the potential to provide personalized treatments based on individual disease profiles, including genomics, and are assisting in medical services. Numerous studies have also identified single-nucleotide polymorphisms (SNPs) associated with the risk of developing RA, as well as epistatic relationships among them. These advancements have the potential to revolutionize early detection and intervention strategies, ultimately leading to better outcomes for patients with RA. However, there are technical challenges to overcome. The application of AI in screening medicinal herbs and addressing these challenges is a future research direction. This chapter presents the role of AI in the diagnosis and treatment of RA, along with future prospects.