Impact of COVID-19 on Society and Review of Machine Learning Algorithms in Diagnosis

The goal of this work is to examine the ways in which machine learning techniques and applications are used for COVID-19 research and other endeavors. More attention has been paid by authorities and researchers to fundamental statistics and epidemiological methods than traditional methods to predict the international COVID-19 epidemic. One of the biggest obstacles to stopping the development of COVID-19 is insufficient and incomplete medical tests to detect and find treatment. To solve this problem, some statistical-based improvements are deployed leading to a partial solution up to a certain level. Machine learning has employed a variety of tactics based on intelligence, methods, and tools to solve problems in the pharmaceutical industry. This work explores how innovative frameworks such as machine learning respond to the difficulties brought on by the COVID-19 epidemic.