Video 1_A machine learning algorithm to predict treatment effectiveness for Kawasaki disease in China: a retrospective model development and validation study.mp4

Video 1_A machine learning algorithm to predict treatment effectiveness for Kawasaki disease in China: a retrospective model development and validation study.mp4

Background<p>Kawasaki disease (KD) is the primary cause of acquired heart disease in children. Intravenous immunoglobulin (IVIG) is the first-line therapy for KD; however, IVIG resistance can occur. Reliable treatment efficacy prediction tools for Chinese patients are lacking, which this study...

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Bibliographische Detailangaben
1. Verfasser: Xuemei Li (232384) (author)
Weitere Verfasser: Zihan Zhou (4184407) (author), Jingyi Fan (8304171) (author), Lin Zhao (92451) (author), Ruidi Xu (16680552) (author), Dong Li (212687) (author), Xu Ma (45624) (author), Lu Sun (194355) (author), Yujian Wu (7515242) (author), Zhouping Wang (1732456) (author), Ce Wang (310582) (author)
Veröffentlicht: 2025
Schlagworte:
Genetic Immunology
Kawasaki disease
IVIG resistance
machine learning
SHAP algorithm
intravenous immunoglobulin
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