Leverage Machine Learning To Infer Proof of the Nipah Influenza

Abstract

Nipah virus is highly fatal virus which spreads from bats to humans & other animals. Due to the fatality of the virus, the aim of this effort is to detect and identify it as soon as possible by understanding the efficiency of machine learning. From the perspective of medicine, the Nipah virus is not treatable using vaccines or medications that have been shown effective. In the field of medicine, machine learning algorithms are crucial for employing ML predictors to isolate the virus in dubious and urgent cases. This technique will produce numerical results to show if a patient has Nipah virus infection or not. Since there is currently no vaccine for the Nipah virus, care must be taken because "prevention is better than cure." To improve model accuracy, more machine learning methods, like Random forest and Decision tree are being applied.