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July 23, 2024Clinical and Experimental PediatricsOpen Access

Construction and validation of predictive models for intravenous immunoglobulin–resistant Kawasaki disease using an interpretable machine learning approach

Linfan Deng Jian Zhao Ting Wang Bin Liu Jun Jiang Peng Jia Dong Liu Gang Li

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Abstract

Intravenous immunoglobulin (IVIG)-resistant Kawasaki disease is associated with coronary artery lesion development.

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Cite This Study

Deng et al. (2024) studied this question.

synapsesocial.com/papers/68e5f61cb6db64358758a1c1 https://doi.org/10.3345/cep.2024.00549

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Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

1Interpretable web-based machine learning model for predicting intravenous immunoglobulin resistance in Kawasaki diseasecohort · 2025 · 8 citations
2Prediction for Intravenous Immunoglobulin Resistance Combining Genetic Risk Loci Identified From Next Generation Sequencing and Laboratory Data in Kawasaki Diseasecase-control · 2020 · 14 citations
3Explainable deep learning algorithm for distinguishing IVIG-Resistant Kawasaki disease in Shandong peninsula, China2025 · 4 citations
4A machine learning algorithm to predict treatment effectiveness for Kawasaki disease in China: a retrospective model development and validation study2025 · 4 citations
5Exploring the diagnostic value of CLR and CPR in differentiating Kawasaki disease from other infectious diseases based on clinical predictive modeling2024 · 5 citations

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Establishment of a Predictive Model for the Response to intravenous immunoglobulin in Children with Kawasaki Disease2026
Establishment and validation of a nomogram for predicting intravenous immunoglobulin resistance and coronary artery lesions involvement in Kawasaki disease: A retrospective study2024
A machine-learning-derived online prediction model for coronary artery aneurysm risk in children with kawasaki disease: a retrospective cohort study2026

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