Interpretable web-based machine learning model for predicting intravenous immunoglobulin resistance in Kawasaki disease

Abstract Background Kawasaki disease (KD) is a leading cause of acquired heart disease in children that is treated with intravenous immunoglobulin (IVIG). However, 10–20% of cases exhibit IVIG resistance, which increases the risk of coronary complications. Existing predictive models do not integrate...

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Detalhes bibliográficos

Principais autores:	Ying He, Fan Lin, Xin Zheng, Qiaobin Chen, Meng Xiao, Xiaoting Lin, Hongbiao Huang
Formato:	Artigo
Idioma:	Inglês
Publicado em:	BMC 2025-06-01
coleção:	Italian Journal of Pediatrics
Assuntos:	Kawasaki disease Immunoglobulins Intravenous Prognosis Machine learning Internet-based intervention
Acesso em linha:	https://doi.org/10.1186/s13052-025-02036-1
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