Data Collected and Analysis of COVID-19 Infection Status: Case Study of Iraqi Hospital Patients in Diwaniyah and Najaf Governorates

Abstract

In recent years, the coronavirus (COVID-19) spread in a dangerous and rapidly. It first appeared in the Chinese city of Wuhan in early December 2019, causing many cases of infection and death because of the rapid spread of the virus throughout the world. The conversion of patient information from paper to electronic helps the medical staff and researchers analyze and retrieve information faster. In this paper, we gathered data about patients infected with COVID-19 who were registered in the Iraqi hospitals of two governorates (Diwaniyah and Najaf) from 2020 to 2023. In addition, we used machine learning algorithms that protect the infection of the data entered for the patient. The highest accuracy (average in both datasets od Diwaniyah and Najaf) ) are achieved by both the algorithms Nave Bayes (90%) and Decision tree (90%) , while the K nearest neighbor (89%), Random forest() and artificial neural network (84).