Explainable machine-learning predictions for complications after pediatric congenital heart surgery

The quality of treatment and prognosis after pediatric congenital heart surgery remains unsatisfactory. A reliable prediction model for postoperative complications of congenital heart surgery patients is essential to enable prompt initiation of therapy and improve the quality of prognosis. Here, we...

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Detalles Bibliográficos
Autores principales: Zeng, Xian, Hu, Yaoqin, Shu, Liqi, Li, Jianhua, Duan, Huilong, Shu, Qiang, Li, Haomin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8390484/
https://www.ncbi.nlm.nih.gov/pubmed/34446783
http://dx.doi.org/10.1038/s41598-021-96721-w

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8390484/
https://www.ncbi.nlm.nih.gov/pubmed/34446783
http://dx.doi.org/10.1038/s41598-021-96721-w

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