An Overview on Covid19 Detection Algorithm Using Deep Learning

Abstract

The epidemic that occurs in any part of today's rapidly globalizing world; It spreads very quickly with strong transportation networks between countries and causes a serious threat to all countries. Due to the rapid spread of the coronavirus and its effects on human health, it was declared a pandemic by the World Health Organization (WHO) on 11 March 2019. Early detection of the disease is very important to prevent the further spread of this epidemic. Thanks to the early diagnosis of positive cases, affected patients can be treated quickly. Serious lung damage can occur in people who contract this disease, which has been declared a pandemic by WHO. The helpful tool that can provide high accuracy and rapid diagnosis of COVID-19 infection is useful for specialist doctors. Doctors diagnose chest diseases with the help of X-Ray Chest X-Ray - (CXR) and Computed Tomography (CT) lung images. Preventive measures can be taken quickly and the diagnosis processes of the physicians can be shortened with an early diagnosis made before the doctor's control for those who are considered to have Covid-19 at the time of CXR images. Artificial intelligence methods are used in the field of health. In addition, these methods give successful results in the diagnosis of many diseases. The application of advanced machine learning and artificial intelligence techniques to images obtained with radiological imaging techniques can help in the accurate detection of Covid-19 disease. CNN techniques have often been used to diagnose Covid-19 disease. The basic features of the images are used to diagnose the Covid-19 disease. Some pre-trained models with a large number of learnable parameters such as AlexNet, GoogleNet, ResNet, VGGNET, and Inception have demonstrated the detection of Covid-19. © 2021 IEEE.