Advertisement
Published in:
2013 | OriginalPaper | Chapter
Periodic Chemotherapy Dose Schedule Optimization Using Genetic Algorithm
Authors : Nadia Alam, Munira Sultana, M. S. Alam, M. A. Al-Mamun, M. A. Hossain
Published in: Distributed Computing and Artificial Intelligence
Publisher: Springer International Publishing
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
This paper presents a design method for optimal cancer chemotherapy schedules using genetic algorithm (GA). The main objective of chemotherapy is to reduce the number of cancer cells or eradicate completely, if possible, after a predefined time with minimum toxic side effects which is difficult to achieve using conventional clinical methods due to narrow therapeutic indices of chemotherapy drugs. Three drug scheduling schemes are proposed where GA is used to optimize the doses and schedules by satisfying several treatment constraints. Finally, a clinically relevant dose scheme with periodic nature is proposed. Here Martin’s model is used to test the designed treatment schedules and observe cell population, drug concentration and toxicity during the treatment. The number of cancer cells is found zero at the end of the treatment for all three cases with acceptable toxicity. So the proposed design method clearly shows effectiveness in planning chemotherapy schedules.