Abstract
In cancer chemotherapy a tumor development is delivered by toxic drugs and the influence of drugs’ on human body is also checked. The minimization of the tumor burden at a fixed period of time and the minimization of the toxicity of drug regimes will be sought corresponding to the mathematical Goempertz growth model. The effective treatment schedules are search with the help of Modified Differential Evolution Multi-Objective Algorithm. The numerical tests of proposed algoritm show the outcomes for each drug regimes. The tumor is eradicated through the treatment period and the toxic effects are small enough according to the strong set of constraints. The simulation of human body answering for different treatment scenarios can help to an oncologist, which can explore treatment schedules before deciding upon admissible doses regimes for suitable clinical treatment.
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Szlachcic, E., Porombka, P., Kotowski, J. (2012). Multi-objective Optimization of Cancer Chemotherapy Treatment. In: Moreno-Díaz, R., Pichler, F., Quesada-Arencibia, A. (eds) Computer Aided Systems Theory – EUROCAST 2011. EUROCAST 2011. Lecture Notes in Computer Science, vol 6928. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27579-1_33
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DOI: https://doi.org/10.1007/978-3-642-27579-1_33
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