An Analysis on Applications of Machine Learning Algorithms to predict COVID-19

Abstract

Machine Learning (ML) has proved itself as an important and distinguished field of study and research over the last decade by explaining and solving many very complex and sophisticated real-world problems. The application regions of ML included practically all this present reality spaces, for example, natural language processing, health care, business applications, autonomous vehicles, climate modelling, gaming, intelligent robots, image and voice processing. One of the most remarkable areas of ML is forecasting. There are loads of studies performed for the forecast of various diseases utilizing ML procedures such as cancer prediction, chronic disease prediction etc. Various standard ML calculations and algorithms have been utilized around there to direct the future course of activities and actions required in numerous applications including disease prediction, stock market prediction and weather forecasting etc. Different regression and neural system models have wide relevance in anticipating the states of patients later on with a particular illness. COVID-19 is presently considered as a potential threat to mankind. A few standard models for COVID-19 are being utilized by authorities around the world for enforcement of relevant control measures. To be explicit the examination will be focussed on the employments of ML on the COVID-19 episode. This study will focus on applications of ML on the healthcare industry pre-pandemic and how the existing methods can be enhanced and used for prediction and detection of COVID-19.