Dialysis adequacy predictions using a machine learning method
Abstract Dialysis adequacy is an important survival indicator in patients with chronic hemodialysis. However, there are inconveniences and disadvantages to measuring dialysis adequacy by blood samples. This study used machine learning models to predict dialysis adequacy in chronic hemodialysis patie...
Enregistré dans:
Auteurs principaux: | Hyung Woo Kim, Seok-Jae Heo, Jae Young Kim, Annie Kim, Chung-Mo Nam, Beom Seok Kim |
---|---|
Format: | article |
Langue: | EN |
Publié: |
Nature Portfolio
2021
|
Sujets: | |
Accès en ligne: | https://doaj.org/article/7e25d2b59aef40c79b19d54c65c0fef6 |
Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
-
Dialysis Adequacy and Risk of Dementia in Elderly Hemodialysis Patients
par: Hyung Woo Kim, et autres
Publié: (2021) -
Machine learning to predict distal caries in mandibular second molars associated with impacted third molars
par: Sung-Hwi Hur, et autres
Publié: (2021) -
Machine learning prediction of dropping out of outpatients with alcohol use disorders.
par: So Jin Park, et autres
Publié: (2021) -
Comparisons of physical activity and understanding of the importance of exercise according to dialysis modality in maintenance dialysis patients
par: Jun Chul Kim, et autres
Publié: (2021) -
Machine learning model to predict hypotension after starting continuous renal replacement therapy
par: Min Woo Kang, et autres
Publié: (2021)