Explainable machine learning model for predicting decline in platelet count after interventional closure in children with patent ductus arteriosus

Explainable machine learning model for predicting decline in platelet count after interventional closure in children with patent ductus arteriosus

BackgroundThis study aimed to apply four machine learning algorithms to develop the optimal model to predict decline in platelet count (DPC) after interventional closure in children with patent ductus arteriosus (PDA).MethodsData from children with PDA who underwent successful transcatheter closure...

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Bibliographic Details
Main Authors: Song-Yue Zhang, Yi-Dong Zhang, Hao Li, Qiao-Yu Wang, Qiao-Fang Ye, Xun-Min Wang, Tian-He Xia, Yue-E He, Xing Rong, Ting-Ting Wu, Rong-Zhou Wu
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-02-01
Series:Frontiers in Pediatrics
Subjects:
children
decline in platelet count
interventional closure
machine learning
patent ductus arteriosus
Online Access:https://www.frontiersin.org/articles/10.3389/fped.2025.1519002/full
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