Improved glomerular filtration rate estimation by an artificial neural network.
BACKGROUND: Accurate evaluation of glomerular filtration rates (GFRs) is of critical importance in clinical practice. A previous study showed that models based on artificial neural networks (ANNs) could achieve a better performance than traditional equations. However, large-sample cross-sectional su...
Main Authors: | Xun Liu, Xiaohua Pei, Ningshan Li, Yunong Zhang, Xiang Zhang, Jinxia Chen, Linsheng Lv, Huijuan Ma, Xiaoming Wu, Weihong Zhao, Tanqi Lou |
---|---|
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2013-01-01
|
Series: | PLoS ONE |
Online Access: | http://europepmc.org/articles/PMC3596400?pdf=render |
Similar Items
-
Improving precision of glomerular filtration rate estimating model by ensemble learning
by: Xun Liu, et al.
Published: (2017-11-01) -
A new equation to estimate glomerular filtration rate in Chinese elderly population.
by: Xun Liu, et al.
Published: (2013-01-01) -
Improving accuracy of estimating glomerular filtration rate using artificial neural network: model development and validation
by: Ningshan Li, et al.
Published: (2020-03-01) -
Using mathematical algorithms to modify glomerular filtration rate estimation equations.
by: Xiaohua Pei, et al.
Published: (2013-01-01) -
Glomerular filtration rates in Asians
by: Teo, B, et al.
Published: (2018)