A Machine Learning Model to Predict Intravenous Immunoglobulin-Resistant Kawasaki Disease Patients: A Retrospective Study Based on the Chongqing Population

Objective: We explored the risk factors for intravenous immunoglobulin (IVIG) resistance in children with Kawasaki disease (KD) and constructed a prediction model based on machine learning algorithms.Methods: A retrospective study including 1,398 KD patients hospitalized in 7 affiliated hospitals of...

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Detalles Bibliográficos
Autores principales:	Jie Liu, Jian Zhang, Haodong Huang, Yunting Wang, Zuyue Zhang, Yunfeng Ma, Xiangqian He
Formato:	article
Lenguaje:	EN
Publicado:	Frontiers Media S.A. 2021
Materias:	machine learning Kawasaki disease intravenous immunoglobulin resistance risk factors prediction model Pediatrics RJ1-570
Acceso en línea:	https://doaj.org/article/5eacca8f125747a398c0e71407d85db0
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A Machine Learning Model to Predict Intravenous Immunoglobulin-Resistant Kawasaki Disease Patients: A Retrospective Study Based on the Chongqing Population

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