Prediction of renal damage in children with IgA vasculitis based on machine learning

This article is objected to explore the value of machine learning algorithm in predicting the risk of renal damage in children with IgA vasculitis by constructing a predictive model and analyzing the related risk factors of IgA vasculitis Nephritis in children. Case data of 288 hospitalized children...

Descripción completa

Detalles Bibliográficos
Autores principales: Wang, Jinjuan, Chu, Huimin, Pan, Yueli
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2022
Materias:
6200
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9592501/
https://www.ncbi.nlm.nih.gov/pubmed/36281102
http://dx.doi.org/10.1097/MD.0000000000031135

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9592501/
https://www.ncbi.nlm.nih.gov/pubmed/36281102
http://dx.doi.org/10.1097/MD.0000000000031135

Ejemplares similares