Application of Machine Learning in Diagnosis of Covid-19 Through X-Ray and Ct Images: A Scoping Review Publisher



Mohammadrahimi H¹ ; Nadimi M^{2, 3} ; Ghalyanchilangeroudi A^{2, 3} ; Taheri M⁴ ; Ghafourifard S⁵ Show Affiliations
Source: Frontiers in Cardiovascular Medicine Published:2021

Abstract

Coronavirus disease, first detected in late 2019 (COVID-19), has spread fast throughout the world, leading to high mortality. This condition can be diagnosed using RT-PCR technique on nasopharyngeal and throat swabs with sensitivity values ranging from 30 to 70%. However, chest CT scans and X-ray images have been reported to have sensitivity values of 98 and 69%, respectively. The application of machine learning methods on CT and X-ray images has facilitated the accurate diagnosis of COVID-19. In this study, we reviewed studies which used machine and deep learning methods on chest X-ray images and CT scans for COVID-19 diagnosis and compared their performance. The accuracy of these methods ranged from 76% to more than 99%, indicating the applicability of machine and deep learning methods in the clinical diagnosis of COVID-19. © Copyright © 2021 Mohammad-Rahimi, Nadimi, Ghalyanchi-Langeroudi, Taheri and Ghafouri-Fard.