Deep Learning Based Examination of Covid19 Disease from Chest X-Ray Database
D Logeshwari, Hebatullah Awwad, Md. Tabil Ahammed, H Pal Thethi, E. Christopher Siddarth, S. Prabha
Abstract
The lung is an important part of the respiratory system, and if you don't address lung disease, which can cause several health issues and could lead to severe berating problems. If you don't get treatment for the lung infection caused by Covid19, it could progress to serious health problems. Hospitals often use medical imaging to find and treat lung diseases. The chest X-ray is a typical way to check for lung problems. This study aims to use Deep-Learning (DL) technology to find lung problems in X-ray pictures. The suggested method has several parts: collecting images and changing their size to 224×224 pixels; extracting features using a chosen DL model; reducing features by 50% dropout and generating fused features; to get better classification. This study used the MobileNet-variant model to look at the X-ray, and the results show that this method can detect things with up to 97% accuracy when SoftMax-based categorisation is used.