Introduction: Dermoscopy has become widespread in the diagnosis of inflammatory skin diseases. Cutaneous vasculitis (CV) is characterized by inflammation of vessels, and a rapid and reliable technique is required for the diagnosis.
Objectives: We aimed to define CV dermoscopic features and increase the diagnostic accuracy of dermoscopy with machine learning (ML) methods.
Background: Chronic spontaneous urticaria (CSU) is a common and disabling disease. Assessments of IgE and C-reactive protein (CRP) are recommended in the diagnostic work-up, but the role and clinical relevance of these biomarkers are not well characterized. Moreover, it remains unknown if elevated levels of IgE or CRP are linked to CSU microRNA (miRNA) signatures or interleukin 31 (IL-31).
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