quote
LaTex
@article{SOHRABI2017126,
title = “Multi-objective feature selection for warfarin dose prediction”,
journal = “Computational Biology and Chemistry”,
volume = “69”,
pages = “126 - 133”,
year = “2017”,
issn = “1476-9271”,
doi = “https://doi.org/10.1016/j.compbiolchem.2017.06.002“,
url = “http://www.sciencedirect.com/science/article/pii/S1476927116303437“,
author = “Mohammad Karim Sohrabi and Alireza Tajik”,
keywords = “Warfarin, Feature selection, Multi-objective optimization, Artificial neural networks”
}
Normal
Mohammad Karim Sohrabi, Alireza Tajik,
Multi-objective feature selection for warfarin dose prediction,
Computational Biology and Chemistry,
Volume 69,
2017,
Pages 126-133,
ISSN 1476-9271,
https://doi.org/10.1016/j.compbiolchem.2017.06.002.
(http://www.sciencedirect.com/science/article/pii/S1476927116303437)
Keywords: Warfarin; Feature selection; Multi-objective optimization; Artificial neural networks
Summary
decision support systems
Drug’s dose prediction
- Mean Square Error (MSE)
- root mean square error (RMSE)
- mean absolute error (MAE)
main content
Multi-Layer Perceptron (MLP)
- filter
- wrapper
- embedded
quantitative structure-activity relationship (QSAR) model
Multiple linear regression (MLR)
partial least squares regression (PLS)
support-vector machine regression (SVMR)
Montecarlo
algorithm
NSGA-II
MOPSO
crowding archive — gbest
concept of the grid — diversity
proposed algorithm
data set
indexes MSE, RMSE and MAE were used to evaluate the network
algorithm
test
