Analysis of COVID-19 Database for Defining the Most Important Symptoms

Abstract

In Wuhan, China, COVID-19 was found at the end of 2019. The virus quickly spread to every country in the world. In order to offer enough treatment at the appropriate time, implementing detection strategies for patient status (Negative, Positive) is one of the top issues for managers and decision-makers in modern hospitals of all sorts.. Enhancing the standard of medical treatment may help to stop a COVID-19 pandemic. A summary of the health care provided to comparable individuals may be obtained by grouping patients with similar characteristics and symptoms. In most cases, algorithms are employed in medical machine learning. This article creates an electronic questionnaire. It covers every nation in the world and is promoted online utilizing Twitter and other networking sites. In the course of getting ready to prepare COVID-19 data, the raw COVID-19 data including non-applicable occurrences is handled after the feedback interpretation and analysis process is complete, after the questionnaires were distributed, and after all the findings have been collated. The patient state is predicted using these traits and symptoms, either positively or negatively.