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- W4313644832 abstract "Abstract Androgen deprivation therapy, also known as hormone therapy, is a standard treatment for prostate cancer, but its 5-year survival rate is only 57 percent. Moreover, the prolonged therapy duration results in increased medication toxicity and drug resistance. A solution to this problem is adaptive therapy, which applies chemotherapy or immunotherapy after hormone therapy is withdrawn. In the proposed work, the idea of adaptive therapy is used by applying nonlinear control algorithms to the proposed ADT model and making the drug dosage based on the control laws that result from applying these algorithms. The overall objective is to reduce the cancer cells to zero in a minimum amount of time to reduce prolonged exposure to drugs. For this, a super-twisting sliding mode controller (STSMC) is applied to reduce the number of androgenindependent (AI) and androgen-dependent (AD) cells. Next, an active control algorithm (ATS)-based Takagi-Sugeno fuzzy controller is introduced and compared to the STSMC design. The ATS fuzzy controller has significantly reduced the therapy duration to two months and is also globally asymptotically stable. Using the Linear Matrix Inequality (LMI) algorithm and the YALMIP toolbox, the controller has been built. Theoretical outcomes are validated using MATLAB and Simulink." @default.
- W4313644832 created "2023-01-07" @default.
- W4313644832 creator A5020064581 @default.
- W4313644832 creator A5037635393 @default.
- W4313644832 date "2023-01-06" @default.
- W4313644832 modified "2023-10-17" @default.
- W4313644832 title "Minimization of Cancer Cells with ATS Fuzzy Controller: An Application to Androgen Deprivation therapy" @default.
- W4313644832 doi "https://doi.org/10.21203/rs.3.rs-2437966/v1" @default.
- W4313644832 hasPublicationYear "2023" @default.
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