Abstract
The paper presents a methodology of using multi-objective differential evolutionary approach to optimize a cancer chemotherapeutic treatment. The structure of optimal and suboptimal solutions will be presented. The constrained Pareto sub-optimal solutions are discussed. The performance assessment of non-dominated and dominated solutions is analyzed to help physicians to choose the most effective solution according to the approximation set of Pareto front.
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Szlachcic, E., & Klempous, R. (2018). Performance Assessment of Optimal Chemotherapy Strategies for Cancer Treatment Planning. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10672 LNCS, pp. 386–393). Springer Verlag. https://doi.org/10.1007/978-3-319-74727-9_46
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