Optimization for Cyclosporine Blood Concentration Prediction Based on Genetic Algorithm - BP Neural Network

被引：1
|
作者：
Li, Shan [1 ]
Chen, Haibing [2 ]
Yun, JunXian [3 ]
Zhou, LiuZheng [4 ]
Xia, Jie [5 ]
Zhang, Jiong [1 ]
Yin, Yasha [1 ]
机构：
[1] Nanjing Med Univ, Dept Comp, Nanjing, Peoples R China
[2] Nanjing Med Univ, Sch Clin 1, Nanjing, Jiangsu, Peoples R China
[3] Beijing Friendship Hosp, Dept Pharm Pediat, Beijing, Peoples R China
[4] Jiangsu Univ, Dept Urinary, Nanjing, Jiangsu, Peoples R China
[5] Nanjing Med Univ, Sch Drug, Nanjing, Jiangsu, Peoples R China
来源：
SECOND INTERNATIONAL CONFERENCE ON GENETIC AND EVOLUTIONARY COMPUTING: WGEC 2008, PROCEEDINGS | 2008年
关键词：
D O I：
10.1109/WGEC.2008.99
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The paper proposes the new model of the genetic algorithm and BP neural networks to predict the blood concentration of Cyclosporine. The BP model was optimized by genetic algorithm to overcome the slower convergence speed, and the best result was found in the particular condition with the strong search function of genetic algorithm. The prediction precision of average blood concentration of Cyclosporine by using the GASP neural network model was 97.5%. It was found that the GABP model was superior to BP neural network in the prediction of Cyclosporine blood concentration. We conclude the GABP model can be used in the prediction of the Cyclosporine blood concentration and help clinicians provide better care for patients taking CsA.
引用
收藏
页码：161 / +
页数：2
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