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...

Descripció completa

Dades bibliogràfiques

Autors principals:	Ying He, Fan Lin, Xin Zheng, Qiaobin Chen, Meng Xiao, Xiaoting Lin, Hongbiao Huang
Format:	Artigo
Idioma:	Inglês
Publicat:	BMC 2025-06-01
Col·lecció:	Italian Journal of Pediatrics
Matèries:	Kawasaki disease Immunoglobulins Intravenous Prognosis Machine learning Internet-based intervention
Accés en línia:	https://doi.org/10.1186/s13052-025-02036-1
Etiquetes:	Afegir etiqueta Sense etiquetes, Sigues el primer a etiquetar aquest registre!