Machine learning-based prediction of acute kidney injury after nephrectomy in patients with renal cell carcinoma

Machine learning-based prediction of acute kidney injury after nephrectomy in patients with renal cell carcinoma

Abstract The precise prediction of acute kidney injury (AKI) after nephrectomy for renal cell carcinoma (RCC) is an important issue because of its relationship with subsequent kidney dysfunction and high mortality. Herein we addressed whether machine learning (ML) algorithms could predict postoperat...

Description complète

Enregistré dans:
Détails bibliographiques
Auteurs principaux: Yeonhee Lee, Jiwon Ryu, Min Woo Kang, Kyung Ha Seo, Jayoun Kim, Jungyo Suh, Yong Chul Kim, Dong Ki Kim, Kook-Hwan Oh, Kwon Wook Joo, Yon Su Kim, Chang Wook Jeong, Sang Chul Lee, Cheol Kwak, Sejoong Kim, Seung Seok Han
Format: article
Langue:EN
Publié: Nature Portfolio 2021
Sujets:
Medicine
R
Science
Q
Accès en ligne:https://doaj.org/article/453c98a5ce9c472bbe11c7f343605b8a
Tags: Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!

Internet

https://doaj.org/article/453c98a5ce9c472bbe11c7f343605b8a

Documents similaires