COVID-19 Detection Based on Chest X-Rays and CT Scans Using Inception v3 Deep Learning Algorithm

Abstract

In December 2019, a number of acute atypical respiratory ailment cases were recorded in Wuhan, China. This swiftly swept throughout China from Wuhan. It wasn't long before a novel coronavirus was identified as the culprit. Among the types of machine learning is deep learning, Deep learning algorithms are designed to automatically learn from large amounts of data, by iteratively improving their ability to identify and extract meaningful features from input data. The majority of COVID-19 symptoms include indicators of respiratory infections and lung abnormalities that radiologists may identify. As a result, Deep Learning algorithms may be used to diagnose illness from pictures of the CT scan and the chest X-ray. To assist radiologists, automated programs might be designed. This article is an effort to diagnose the sickness using the Deep Learning algorithm Inception V3. The method was tested on two types of databases: X-rays of the chest and CT scans. The results demonstrated that the procedure was successful and that the results were improved when applied to the Chest X-ray datasets.

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