Machine learning to predict end stage kidney disease in chronic kidney disease

The purpose of this study was to assess the feasibility of machine learning (ML) in predicting the risk of end-stage kidney disease (ESKD) from patients with chronic kidney disease (CKD). Data were obtained from a longitudinal CKD cohort. Predictor variables included patients’ baseline characteristi...

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Detalles Bibliográficos
Autores principales: Bai, Qiong, Su, Chunyan, Tang, Wen, Li, Yike
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9120106/
https://www.ncbi.nlm.nih.gov/pubmed/35589908
http://dx.doi.org/10.1038/s41598-022-12316-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9120106/
https://www.ncbi.nlm.nih.gov/pubmed/35589908
http://dx.doi.org/10.1038/s41598-022-12316-z

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