DETECTION OF EXANTHEMATOUS SYNDROME IN CHILDREN WITH COVID-19 USING ARTIFICIAL INTELLIGENCE

The COVID-19 pandemic has profoundly affected healthcare systems worldwide. In children, the clinical symptoms of COVID-19 often vary from those observed in adults, with one significant manifestation being exanthematous syndrome, which presents as skin rashes or lesions related to the infection [1]. Diagnosing this syndrome can be complex, as it may mimic allergic reactions, viral rashes, or other medical conditions. The emergence and evolution of artificial intelligence (AI) in the medical field provide new avenues for improving diagnostic precision, prognosis, and treatment strategies. This study seeks to assess how effective AI technologies are in identifying exanthematous syndrome in pediatric COVID-19 patients [2]. The aim of this study is to utilize artificial intelligence (AI) methods for detecting exanthematous syndrome in children infected with COVID-19. This approach not only enhances the accuracy and timeliness of diagnosis but also deepens the understanding of the virus's pathogenesis in the pediatric population. This article presents an overview of the problem, the research methodology, the results of applying AI in diagnosing exanthematous syndrome, and a discussion of these findings in the context of their practical application in pediatric practice.