4.8 Article

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

Journal

CELL
Volume 181, Issue 6, Pages 1423-+

Publisher

CELL PRESS
DOI: 10.1016/j.cell.2020.04.045

Keywords

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Funding

  1. National Key Research and Development Program of China [2019YFB1404804]
  2. National Natural Science Foundation of China [61906105, 61872218, 61721003, 61673241, 81871890, 91859203]
  3. Macao FDCT grant [0035/2020/A]
  4. Guangzhou Regenerative Medicine and Health Guangdong Laboratory [2020GZR110306001]
  5. Kunmin Science and Technology grant [2020-1-H003]
  6. Special Item for Prevention and Control of COVID-19 Science and Technology, Guangdong Province
  7. Tencent Charity Foundation
  8. Sun Yat-sen University for novel coronavirus, The Key Areas Research and Development Program of Guangdong [2018B010109006]
  9. Guangdong Provincial Clinical Research Center for Urinary Diseases, Recruitment Program of Leading Talent in Guangdong Province [2016LJ06Y375]

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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.

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