Prediction of dialysis adequacy using data-driven machine learning algorithms

Prediction of dialysis adequacy using data-driven machine learning algorithms

Background Adequate delivery of hemodialysis (HD), measured by the spKt/V derived from urea reduction, is an important determinant of clinical outcomes in chronic hemodialysis patients. However, the need for pre- and postdialysis blood samples prevented the assessment of spKt/V in every session.Meth...

Full description

Saved in:
Bibliographic Details
Main Authors: Yi-Chen Liu, Ji-Ping Qing, Rong Li, Juan Chang, Li-Xia Xu
Format: Article
Language:English
Published: Taylor & Francis Group 2024-12-01
Series:Renal Failure
Subjects:
Dialysis adequacy
Kt/V
machine learning
hemodialysis
Online Access:https://www.tandfonline.com/doi/10.1080/0886022X.2024.2420826
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items

Similar Items