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

BACKGROUND: Short-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...

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Detalles Bibliográficos
Autores principales: Duan, Minjie, Shu, Tingting, Zhao, Binyi, Xiang, Tianyu, Wang, Jinkui, Huang, Haodong, Zhang, Yang, Xiao, Peilin, Zhou, Bei, Xie, Zulong, Liu, Xiaozhu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Cardiovascular Medicine
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9360407/
https://www.ncbi.nlm.nih.gov/pubmed/35958416
http://dx.doi.org/10.3389/fcvm.2022.919224

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9360407/
https://www.ncbi.nlm.nih.gov/pubmed/35958416
http://dx.doi.org/10.3389/fcvm.2022.919224

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