Modeling and control of chemotherapy drug release system for brain tumor treatment

Brain tumors are among the types of cancer with high mortality rates, which complicate early diagnosis and effective treatment processes due to the complex structure of the central nervous system. Chemotherapy, one of the most used methods in the treatment process, can also affect healthy cells and suppress the patient's immune system. Therefore, it is of great importance to control the dosage of chemotherapy drugs in a personalized, safe, and optimal manner. In this study, a Type-2 Fuzzy Logic Controller (T2FLC) was designed to control the chemotherapy drug dosage in the treatment of brain tumors. It has been shown that T2FLC provides more flexible and precise control mechanisms thanks to its ability to better handle uncertainties in membership functions. The parameters of the control system were optimized using the Artificial Hummingbird Algorithm (AHA), a new generation algorithm inspired by nature, and the Particle Swarm Optimization (PSO) algorithm, which is widely used in literature.