Transforming Rheumatoid Arthritis Management: Harnessing Artificial Intelligence for Early Detection, Personalized Treatment, and Ethical Challenges

Abstract

Rheumatoid arthritis (RA) is one of the several autoimmune rheumatic diseases affecting a large population of patients; it presents with multiple comorbidities and complications and is, therefore, difficult to diagnose, treat and manage. It is acknowledged that the application of artificial intelligence (AI) in different areas of RA research and clinical management provides hopeful approaches to these challenges. This review aims to give a systematic information about the existing studies that addresses the implementation of AI into the RA including early detection, prognosis, treatment planning and decision making, drug development, and patient counselling. Substantial emphasis is placed on ML, DL, and NLP, which are instrumental in increasing diagnostic reliability, refining treatment management, and increasing patient involvement. In term of drug discovery, AI enhances speed of identifying new therapeutic agents and repurposing known medicines in treating new disorders by exploring big data and predicting drug-target relations. Artificial intelligence has progressed into using genetic and biomarker information and predicting potential biomarkers and genetic risk factors that leads to development of RA personalized drugs and intervention plan. Additionally, AI has been used in remote care and tele medicine and tele health services, enabling better treatment, diagnosis and prognosis for patients who are hard to reach or have challenges getting the access to better healthcare. However, there are some challenges in using of AI in the process of RA. The issues of data protection; data collection and management consent, and bias within AI models and systems must be dealt to make AI fair, open, and advantageous to every patient.

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