Perbandingan Metode Extended Kalman Filter dan Ensamble Kalman Filter dalam Mengestimasi Pertumbuhan Sel Kanker dengan Pengobatan Virus Oncolytic - Rifki Ilham Baihaki; Didik Khusnul Arif; Erna Apriliani (CGANT JOURNAL OF MATHEMATICS AND APPLICATIONS, 2023)
Virus is a microorganism that can spread and infect living cells, such as humans, animals, and plants. Not all viruses have negative effects, as in the case of oncolytic viruses. This type of virus is modified to infect and kill cancer cells. The success of cancer therapy using this virus depends on the pattern of interaction between the virus population and cancer cells, which can be described by a mathematical model. This research uses two methods to estimate the growth of cancer cells with oncolytic virus therapy, namely the Extended Kalman Filter (EKF) and the Ensemble Kalman Filter (EnKF). The results show that EKF has a faster computation time compared to EnKF. However, the EKF estimation results are still inferior to those of EnKF.