Shark Optimization Algorithm: Drug Dosage Estimation in Cancer Chemotherapy

Chemotherapy is a medicine that is frequently exploited to treat cancer; the cancer cells widen as well as propagate more rapidly than the other cells in body. Although chemotherapy is a capable technique to analyze several types of cancers, treatment involves threat as it reasons side effects because of inappropriate drug practice. Thus, this research proposes a robust controller to control the dosage of the drug which is performed in parameter estimation. Additionally, a Modified Regularized Error Function (MREF)-Extended Kalman Filter (EKF) is adopted to approximate tumor cells as well as it can be used for different circumstances. In addition, the overfitting problem happens at the time of the drug dosage estimation which is resolved by exploiting this method. Furthermore, to improve the proposed model performance, the primary condition of EKF is fine-tuned using Shark Optimization Algorithm (SOA). Finally, the preeminence of the developed technique is revealed regarding the error analysis.