Explainable machine learning models for predicting 30-day readmission in pediatric pulmonary hypertension: A multicenter, retrospective study

BackgroundShort-term readmission for pediatric pulmonary hypertension (PH) is associated with a substantial social and personal burden. However, tools to predict individualized readmission risk are lacking. This study aimed to develop machine learning models to predict 30-day unplanned readmission i...

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Detalhes bibliográficos

Principais autores:	Minjie Duan, Tingting Shu, Binyi Zhao, Tianyu Xiang, Jinkui Wang, Haodong Huang, Yang Zhang, Peilin Xiao, Bei Zhou, Zulong Xie, Xiaozhu Liu
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Frontiers Media S.A. 2022-07-01
coleção:	Frontiers in Cardiovascular Medicine
Assuntos:	pediatric pulmonary hypertension readmission machine learning prediction risk factors
Acesso em linha:	https://www.frontiersin.org/articles/10.3389/fcvm.2022.919224/full
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