Slow-down COVID-19


AI app for screening of mild pneumonia using portable Chest X-ray (CXR) geared towards epidemiological control of COVID19 in a pre-clinical settings.

How does it work?

Covictory App for CXR early pneumonia screening

Covictoryapp workflow


On March 11, WHO declared COVID19 a pandemic. Since then, public health officials have faced tough decision aimed at controling the pandemic by means of social distancing, confinement and isolation of positives cases. This extreme measurements try to content the infectious curve by reducting the contagious rate so the heatlh care systems can meet the unforseen and striking high demand.

Early detection and screening is critical to manage the pandemic from a public health perspective. It will be even more important in the second phase of this crisis when public health officials decide to progressively stop the strict confimenent measurements. Pandemic control measurements will be in need.

Pandemic control phases

The definitive test for SARS-CoV-2 is the real-time reverse transcriptase-polymerase chain reaction (RT-PCR) test. However, radiographic findings have been reported as a potential tool for screening. The typical radiographic findings that have been reported are:

The main caractheristics of a pandemic control tool should be

While point of care (PoC) molecular testing can fulfill this need in the longer term, they are still being developed and approved. CXR can serve as a testing surrogate for early population management to provide a massive screening tool if automatic interpretation is available.

“Covictory” App

We have devleoped a free stand-alone client-based web tool for automatic early detection of mild pneumonia from CXR images to help prevent the epidemic. Beta test version

Covictory App Beta test

AI Engine

We have used three major public X-ray databases to isolate cases with pneumonia. We have further subclassified those cases signs of mild vs. moderate/severe pneumonia to train an artificial intelligence system that can detect early pneumonia as a potential sign of COVID19 infection and health status worsening. The network that we have impletemed is inspired on an efficient network architecture

Performance characteristics

Testing set (20% of data that was not used for training)

Performance characteristics

  AUC Sensitivity Specificity Probability Threshold
Control vs. All pneumonias 96.2% 90.3% 92.1% 0.43
Control vs. Mild 95.7% 88.7% 91.78% 0.36
Mild vs. Moderate-Severed 86.1% 78.3% 78.7% 0.05

Support and Contact

This tool has been developed by the team of researchers at the Applied Chest Imaging Laboratory.

Code and models are open-source and to enable system integration:

Contact information: Raul San Jose Estepar


This is not meant to be a diagnostic tool. This tool has not been certified by any agency and is not considered a medical device.

Developing Team


This work has been performed in kind under NIH funding.

Data sharing resources