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About the solution
Researchers from the University of Waterloo Vision and Image Processing Lab and the startup DarwinAI partnered to create COVID-Net - a convolutional neural network for COVID-19 detection from chest radiographies.
They started working on this project with the objective of using their expertise to develop an AI-based tool that could help in the screening and diagnosis of patients for Covid-19.
The COVID-Net tool was trained and tested through the COVIDx dataset – an open resource that hold more than 16.000 chest x-rays from over 13.000 patient cases. These test determined that COVID-Net was able to detect Covid-19 infections with a PPV (Positive Predictive Value) of 88,9%.
The project is on-going and the models provided are meant to be used as a reference and improved upon as new data is made available.
The COVID-19 project is completely open source, with the codes, documentation, dataset, and scientific papers available at the GitHub website.
Adapted from:https://syncedreview.com/2020/04/02/darwinai-open-sources-covid-net-as-m...
Project Page at Github for more information: https://github.com/lindawangg/COVID-Net
This solution shall not include mention to the use of drugs, chemicals or biologicals (including food); invasive devices; offensive, commercial or inherently dangerous content. This solution was not medically validated. Proceed with caution! If you have any doubts, please consult with a health professional.
DISCLAIMER: This story was written by someone who is not the author of the solution, therefore please be advised that, although it was written with the utmost respect for the innovation and the innovator, there can be some incorrect statements. If you find any errors please contact the patient Innovation team via info@patient-innovation.com
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