Clinically Applicable AI System for Accurate Diagnosis, Quantitative Measurements, and Prognosis of COVID-19 Pneumonia Using Computed Tomography

Cell. 2020 Jun 11;181(6):1423-1433.e11. doi: 10.1016/j.cell.2020.04.045. Epub 2020 May 4.


Many COVID-19 patients infected by SARS-CoV-2 virus develop pneumonia (called novel coronavirus pneumonia, NCP) and rapidly progress to respiratory failure. However, rapid diagnosis and identification of high-risk patients for early intervention are challenging. Using a large computed tomography (CT) database from 3,777 patients, we developed an AI system that can diagnose NCP and differentiate it from other common pneumonia and normal controls. The AI system can assist radiologists and physicians in performing a quick diagnosis especially when the health system is overloaded. Significantly, our AI system identified important clinical markers that correlated with the NCP lesion properties. Together with the clinical data, our AI system was able to provide accurate clinical prognosis that can aid clinicians to consider appropriate early clinical management and allocate resources appropriately. We have made this AI system available globally to assist the clinicians to combat COVID-19.

Keywords: AI; COVID-19; SARS-CoV-2; automated diagnosis; computed tomography; deep learning; pneumonia; prognosis analysis.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Artificial Intelligence*
  • COVID-19
  • China
  • Cohort Studies
  • Coronavirus Infections / diagnosis*
  • Coronavirus Infections / pathology
  • Coronavirus Infections / therapy
  • Datasets as Topic
  • Humans
  • Lung / pathology
  • Models, Biological
  • Pandemics
  • Pilot Projects
  • Pneumonia, Viral / diagnosis*
  • Pneumonia, Viral / pathology
  • Pneumonia, Viral / therapy
  • Prognosis
  • Radiologists
  • Respiratory Insufficiency / diagnosis
  • Tomography, X-Ray Computed*