Optimal adaptive intuitionistic fuzzy logic control of anti-cancer drug delivery systems

Publication date: April 2020Source: Biomedical Signal Processing and Control, Volume 58Author(s): Mohamed Esmail Karar, Ahmed Hamdy El-Garawany, Mohamed El-BrawanyAbstractThis paper introduces a new closed loop fuzzy logic controller for regulating intravenous anti-cancer drug delivery, based on intuitionistic fuzzy sets and invasive weed optimization (IWO) algorithm. The developed intuitionistic fuzzy logic controller (IFLC) contributes the following advancements: First, the parameters of IFLC are adaptive and optimally tuned to achieve desired drug concentrations at the tumor site, killing almost all cancer cells at the end of treatment time. Second, drug delivery constraints; namely allowed levels of the drug dose and cumulative toxicity are naturally implied in the design of the optimized IFLC to ensure the clinical safety of cancer patients. Finally, the developed drug delivery control system is robust to handle all possible physiological conditions during treatment such as patient sensitivity in response to toxicity. To test and validate the performance of developed IFLC, extensive simulation results and comparative evaluation have been done on a mathematical patient model. It is proved that our optimal adaptive IFLC is superior to other methods in previous related studies, resulting in the best performance index and the minimum number of remaining cancer cells of 27.63 and 0.806, respectively.
Source: Biomedical Signal Processing and Control - Category: Biomedical Science Source Type: research