DocumentCode
2915350
Title
Optimisation of cancer chemotherapy schedules using directed intervention crossover approaches
Author
Godley, Paul ; Cowie, Julie ; Cairns, David ; McCall, John ; Howie, Catherine
Author_Institution
Dept. of Comput. Sci. & Math., Stirling Univ., Stirling
fYear
2008
fDate
1-6 June 2008
Firstpage
2532
Lastpage
2537
Abstract
This paper describes two directed intervention crossover approaches that are applied to the problem of deriving optimal cancer chemotherapy treatment schedules. Unlike traditional uniform crossover (UC), both the calculated expanding bin (CalEB) method and targeted intervention with stochastic selection (TInSSel) approaches actively choose an intervention level and spread based on the fitness of the parents selected for crossover. Our results indicate that these approaches lead to significant improvements over UC when applied to cancer chemotherapy scheduling.
Keywords
cancer; optimisation; radiation therapy; scheduling; stochastic processes; calculated expanding bin method; cancer chemotherapy schedule optimisation; chemotherapy treatment schedules; directed intervention crossover approaches; targeted intervention with stochastic selection; uniform crossover; Cancer; Drugs; Evolutionary computation; Mathematical model; Medical treatment; Protection; Scheduling algorithm; Stochastic processes; Testing; Vehicle dynamics;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). IEEE Congress on
Conference_Location
Hong Kong
Print_ISBN
978-1-4244-1822-0
Electronic_ISBN
978-1-4244-1823-7
Type
conf
DOI
10.1109/CEC.2008.4631138
Filename
4631138
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