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

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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Bibliographic Details
Main Authors: Jie Liu, Jian Zhang, Haodong Huang, Yunting Wang, Zuyue Zhang, Yunfeng Ma, Xiangqian He
Format: article
Language:EN
Published: Frontiers Media S.A. 2021
Subjects:
machine learning
Kawasaki disease
intravenous immunoglobulin resistance
risk factors
prediction model
Pediatrics
RJ1-570
Online Access:https://doaj.org/article/5eacca8f125747a398c0e71407d85db0
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https://doaj.org/article/5eacca8f125747a398c0e71407d85db0

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