ANALYZING THE LEVEL OF INFLAMMATION IN RHEUMATOLOGICAL DISEASES USING AI

• Davlataliyev Xolidbek

  Student of Group 109 Tashkent, Uzbekistan Tashkent State Medical University Faculty of General Medicine No.1

  Author

• Fazliddin Arzikulov

  Assistant of the Department of Biomedical Engineering, Informatics, and Biophysics at Tashkent State Medical University

  Author

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.

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