ANALYZING THE LEVEL OF INFLAMMATION IN RHEUMATOLOGICAL DISEASES USING AI
Keywords:
Artificial intelligence; Rheumatology; Chronic inflammation; Machine learning; Deep learning; Biomarkers; Medical imaging; Disease activity; Personalized medicine.Abstract
Rheumatological diseases are chronic, immune-mediated conditions characterized by inflammation affecting joints, connective tissues, and systemic organs. Accurate assessment of inflammation is central to diagnosis, disease activity monitoring, prognosis, and therapeutic decision-making. Traditional methods—such as clinical examination, laboratory markers, and imaging—have significant limitations, including subjectivity, delayed response, and inability to capture disease heterogeneity. Artificial Intelligence (AI) has emerged as a transformative tool capable of integrating complex, multimodal data to improve the assessment of inflammation in rheumatological diseases. This article explores the role of AI in inflammation analysis, including its applications in clinical data interpretation, imaging, biomarkers, genomics, and personalized medicine, while also addressing challenges, ethical considerations, and future directions.
