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|Title:||Automating the drug scheduling of cancer chemotherapy via evolutionary computation|
|Authors:||Tan, K.C. |
Distributed evolutionary computing
|Citation:||Tan, K.C., Khor, E.F., Cai, J., Heng, C.M., Lee, T.H. (2002). Automating the drug scheduling of cancer chemotherapy via evolutionary computation. Artificial Intelligence in Medicine 25 (2) : 169-185. ScholarBank@NUS Repository. https://doi.org/10.1016/S0933-3657(02)00014-3|
|Abstract:||This paper presents the optimal control of drug scheduling in cancer chemotherapy using a distributed evolutionary computing software. Unlike conventional methods that often require gradient information or hybridization of different approaches in drug scheduling, the proposed evolutionary optimization methodology is simple and capable of automatically finding the near-optimal solutions for complex cancer chemotherapy problems. It is shown that different number of variable pairs in evolutionary representation for drug scheduling can be easily implemented via the software, since the computational workload is shared and distributed among multiple computers over the Internet. Simulation results show that the proposed evolutionary approach produces excellent control of drug scheduling in cancer chemotherapy, which are competitive or equivalent to the best solutions published in literature. © 2002 Elsevier Science B.V. All rights reserved.|
|Source Title:||Artificial Intelligence in Medicine|
|Appears in Collections:||Staff Publications|
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