Virus is a microorganism that can spread and infect living cells, suchas humans, animals, and plants. Not all viruses have negative effects, as in thecase of oncolytic viruses. This type of virus is modified to infect and kill cancercells. The success of cancer therapy using this virus depends on the pattern ofinteraction between the virus population and cancer cells, which can bedescribed by a mathematical model. This research uses two methods to estimatethe growth of cancer cells with oncolytic virus therapy, namely the ExtendedKalman Filter (EKF) and the Ensamble Kalman Filter (EnKF). The results showthat EKF has a faster computation time compared to EnKF. However, the EKFestimation results are still inferior to those of EnKF.
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