Healthcare case study: COVID19 detection, prevention measures, and prediction using machine learning & deep learning algorithms

ABSTRACT

In healthcare, COVID19 has been spreading in multiple forms across the entire world. Coronavirus, or COVID19, belongs to a large group of viruses that are the causes for mild respiratory tract infections in humans, varying from the common cold, or can be more severe like Severe Acute Respiratory Syndrome (SARS) and Middle Eastern Respiratory Syndrome (MERS). This work aims to provide information about symptoms of coronavirus, its detection, and its prevention. In this study, we proposed a model for predicting results. Predictions are made using patients' symptoms of having Covid19 or not by applying various machine learning and deep learning algorithms. The effectiveness of the proposed model is experimentally evaluated on patients' symptoms using 5000 rows of a data set. Many cases are highlighted as a group of problems related to the COVID19 pandemic and point out promising results. © 2022 Scrivener Publishing LLC.