Application of Machine Learning in Diagnosis of COVID-19 Through X-Ray and CT Images: A Scoping Review

Frontiers in Cardiovascular Medicine

卷:8

Hossein Mohammad-Rahimi¹  Soudeh Ghafouri-Fard²  Azadeh Ghalyanchi-Langeroudi⁴  Mohadeseh Nadimi⁴  Mohammad Taheri⁵ 

[1] Dental Research Center, Research Institute of Dental Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran;

[2] Department of Medical Genetics, Shahid Beheshti University of Medical Sciences, Tehran, Iran;

[3] Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences (TUMS), Tehran, Iran;

[4] Research Center for Biomedical Technologies and Robotics (RCBTR), Tehran, Iran;

[5] Urology and Nephrology Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran;

关键词: COVID-19;    machine learning;    detection;    biomarker;    X-ray image;   

DOI  :  10.3389/fcvm.2021.638011

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown