COVID-Net: an open source neural network for COVID-19 detection

Sheldon Fernandez
Mar 23, 2020 · 1 min read

Note: since this post was published there’ve been a number of developments to the project. See here for the latest.

Dear Colleague,

The global crisis brought on by COVID-19 has affected us all.

Like many businesses, we’ve been grappling with how to best deploy our skills in service of the present crisis.

To this end, we have collaborated with researchers at the University of Waterloo’s VIP Lab to develop COVID-Net: a convolutional neural network for COVID-19 detection via chest radiography. We’ve also compiled together COVIDx, a dataset with 5941 posteroanterior chest radiography images across 2839 patient cases gathered from public sources.

We are open sourcing this model to the community in hopes of developing a robust tool to assist health care professionals in combating the pandemic.

The source code, documentation, dataset, and scientific paper describing COVID-Net are available at this GitHub repo.

In addition, if you are a researcher or clinician and would like access to our explainability platform to assist with this project and gain transparency on how COVID-Net detects COVID-19 infections, or have COVID-19 data that you wish to share, please email us at info@darwinai.ca.

In Solidarity,

The DarwinAI team

Example chest radiography images of COVID-19 cases from 2 different patients and their associated critical factors (highlighted in red) as identified by GSInquire

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