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

Abstract

COVID-19 was discovered near the end of 2019 in Wuhan, China. In a short period, the virus had spread throughout the entire world. One of the primary concerns of managers and decision-makers in all types of hospitals nowadays is to implement detection plans for status of patient (Negative, Positive) in order to provide enough care at the proper moment. To reduce a pandemic of COVID-19, improving health care quality could be advantageous. Making clusters of patients with similar features and symptoms supplies an overview of health quality given to similar patients. algorithms are usually used medical machine learning.In this paper,  ​a questionnaire electronic is created It includes all countries of the world and Promote it via the Internet using social networking sites and Twitter. After procedure of feedback interpretation and analysis has been completed once the questionnaires were sent out and all the results collated, the raw covid-19 data comprising non-applicable occurrences is processed as part of the COVID-19 data preparation procedure. These characteristics and symptoms are used to forecast whether the patient status is negative or positive.