• Chest X-rays have been proposed as a potentially useful tool for assessing COVID-19 patients, especially in overwhelmed emergency departments and urgent care centers.
  • Chest X-ray abnormalities from COVID-19 appear very similar to those of TB patients.
  • Hypothesis: a deep learning model already trained to identify TB in X-rays would also work well to identify signs of the novel coronavirus.


  • Paper published in the Journal for Thoracic Imaging 
  • Collected 88 publicly available frontal chest X-rays from patients with confirmed COVID-19 diagnoses
  • Of the 88, the model correctly classified 78 of them as “positive” for COVID-19, for an 89 percent success rate.
  • Results are a proof-of-concept for a potential new screening method for COVID-19 in clinical settings. Deep learning models could facilitate faster triage in emergency departments, point-of-care interpretation for non-radiologists on the frontline, and potential workload reduction for radiologists.
Algorithm localizing COVID-19 pneumonia on chest x-ray

Algorithm localizing COVID-19 pneumonia on chest x-ray



Paul Yi, radiology resident and co-Director of the Radiology AI Lab

Tae Kyung Kim, medical student at Johns Hopkins School of Medicine

Cheng Ting Lin, director of Thoracic Radiology in the Russell H. Morgan Department of Radiology and Radiological Science