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A novel approach to optimize combinatory drugs using Markov chain
Wang B(王博); Wang WX(王文学); Wang YC(王越超); Liu LQ(刘连庆)
作者部门机器人学研究室
会议名称2016 IEEE 11th Annual International Conference on Nano/Micro Engineered and Molecular Systems (NEMS)
会议日期April 17-20, 2016
会议地点Sendai, Japan
会议录名称Proceedings of the 11th IEEE Annual International Conference on Nano/Micro Engineered and Molecular Systems (NEMS)
出版者IEEE
出版地New York
2016
页码18-23
收录类别EI ; CPCI(ISTP)
EI收录号20165203189783
WOS记录号WOS:000391893400005
产权排序1
ISBN号978-1-5090-1948-9
摘要Combinatory drugs are often used in clinical medications for treating some complex diseases such as cancer, diabetes, etc. An extreme challenge in combinatory therapy is that the number of combinations will increase exponentially as the types of drugs increase, which makes it very difficult to choose the optimal concentration. In this paper, we present a new algorithm based on the stationary distribution of Markov chain to optimize combinatory drugs. We evaluated the new algorithm by comparing its performance with the other two stochastic algorithms, the Gur Game algorithm and the modified Gur Game algorithm. Numerical simulations clearly show that the algorithm based on Markov chain has a better performance than these two stochastic algorithms, in terms of both reliability and efficiency. This work provides a general method for the combinatorial optimization problem, and it is meaningful for clinical combinatory therapy.
语种英语
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文献类型会议论文
条目标识符http://ir.sia.cn/handle/173321/19568
专题机器人学研究室
通讯作者Wang WX(王文学); Liu LQ(刘连庆)
作者单位1.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, 110016, China
2.University of Chinese Academy of Sciences, Beijing, 100049, China
推荐引用方式
GB/T 7714
Wang B,Wang WX,Wang YC,et al. A novel approach to optimize combinatory drugs using Markov chain[C]. New York:IEEE,2016:18-23.
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