Advances in the Co-Host Immune Response to Multisystem Inflammatory Syndrome and Kawasaki Disease in Children with AI-Guided Features

Abstract

Purpose: To explore the role of artificial intelligence in the immune response mechanism of children with multi-system inflammatory syndrome and Kawasaki disease. Methods: To search the domestic and foreign literatures about the immune response mechanism of these two diseases, and analyze the literatures according to the characteristics of artificial intelligence. Results: AI analysis showed that the two kinds of children's syndrome were concentrated in the cytokine storm centered on il-15/IL15RA, which confirmed that the two diseases had the same initial immune pathway, but the differences in immune phenotype, cytokine, cell count and other aspects suggested that KD and MIS-C were two different diseases. Conclusion: It shows the applicability of AI in this research direction, and points out the limitations of the current research scope and samples. The difference between the results of KD and MIS-C research guides the direction of future research. Accurate and comprehensive laboratory indicators and parameters can be applied to artificial intelligence and provide basis for diagnosis and treatment of diseases. As the number of infected people increases, the problem of sample limitation in the current work can also be improved.