Review on Diagnosis of COVID-19 from Chest CT Images Using Artificial Intelligence

Comput Math Methods Med. 2020 Sep 26:2020:9756518. doi: 10.1155/2020/9756518. eCollection 2020.

Abstract

The COVID-19 diagnostic approach is mainly divided into two broad categories, a laboratory-based and chest radiography approach. The last few months have witnessed a rapid increase in the number of studies use artificial intelligence (AI) techniques to diagnose COVID-19 with chest computed tomography (CT). In this study, we review the diagnosis of COVID-19 by using chest CT toward AI. We searched ArXiv, MedRxiv, and Google Scholar using the terms "deep learning", "neural networks", "COVID-19", and "chest CT". At the time of writing (August 24, 2020), there have been nearly 100 studies and 30 studies among them were selected for this review. We categorized the studies based on the classification tasks: COVID-19/normal, COVID-19/non-COVID-19, COVID-19/non-COVID-19 pneumonia, and severity. The sensitivity, specificity, precision, accuracy, area under the curve, and F1 score results were reported as high as 100%, 100%, 99.62, 99.87%, 100%, and 99.5%, respectively. However, the presented results should be carefully compared due to the different degrees of difficulty of different classification tasks.

Publication types

  • Review

MeSH terms

  • Artificial Intelligence
  • Betacoronavirus*
  • COVID-19
  • COVID-19 Testing
  • Clinical Laboratory Techniques*
  • Coronavirus Infections / diagnosis
  • Coronavirus Infections / diagnostic imaging*
  • Coronavirus Infections / epidemiology
  • Deep Learning
  • Humans
  • Neural Networks, Computer
  • Pandemics*
  • Pneumonia / classification
  • Pneumonia / diagnostic imaging
  • Pneumonia, Viral / diagnostic imaging*
  • Pneumonia, Viral / epidemiology
  • Radiographic Image Interpretation, Computer-Assisted / methods*
  • Radiographic Image Interpretation, Computer-Assisted / statistics & numerical data
  • Radiography, Thoracic / statistics & numerical data
  • SARS-CoV-2
  • Sensitivity and Specificity
  • Tomography, X-Ray Computed / statistics & numerical data*