Kawasaki Disease: Unraveling Immunopathogenesis, Genetic Factors, and AI Applications in Diagnosis with a Focus on Iran.

Kawasaki disease (KD) is an acute multisystem vasculitis that represents the leading cause of acquired pediatric heart disease in children aged 1-5 years in developed nations. The diagnosis of KD remains clinically challenging due to its diverse clinical manifestations and the absence of definitive laboratory tests. Growing evidence suggests that inflammatory processes play a pivotal role in the pathogenesis of KD, implicating a significant involvement of the immune system in disease development. Given the established associations between KD and various biomarkers, ranging from genetic factors to immune system components, this review systematically examines the current knowledge on the immunological and genetic aspects of KD, with a particular focus on the Iranian population. Meanwhile, artificial intelligence (AI) may be revolutionized disease diagnosis, prognosis, and predictive modeling. Its applications have extended to KD, including early detection and classification, as briefly discussed in this review. By synthesizing existing evidence, we aim to identify critical research gaps and enhance understanding of KD's unique characteristics in this demographic context.