Optimal control of a cancer chemotherapy problem with different toxic elimination processes
Refereed conference paper presented and published in conference proceedings


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摘要In this paper, we propose two new anticancer drug scheduling models with different toxicity clearances according to kinetics of enzyme-catalyzed chemical reactions. We also present a sophisticated automating drug scheduling approach based on evolutionary computation and computer modeling. To explore multiple efficient drug scheduling policies, we use a multimodal optimization algorithm - adaptive elitist-population based genetic algorithm (AEGA) to solve the models, and discuss the situation of multiple optimal solutions under different parameter settings. The simulation results obtained by the new models match well with the clinical treatment experience, and can provide much more drug scheduling policies for a doctor to choose depending on the particular conditions of the patients.
著者Liang Y, Leung KS, Mok TSK
會議名稱IEEE Congress on Evolutionary Computation
會議開始日16.07.2006
會議完結日21.07.2006
會議地點Vancouver
會議國家/地區加拿大
詳細描述organized by IEEE Congress,
出版年份2006
月份1
日期1
出版社IEEE
頁次2460 - 2467
國際標準書號978-0-7803-9487-2
語言英式英語
Web of Science 學科類別Computer Science; Computer Science, Artificial Intelligence; Computer Science, Theory & Methods

上次更新時間 2020-13-10 於 00:17