id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-189307-qb0s06tl	Wang, Linda	COVID-Net: A Tailored Deep Convolutional Neural Network Design for Detection of COVID-19 Cases from Chest X-Ray Images	2020-03-22		.txt	text/plain	4338	171	42	Motivated by this and inspired by the open source efforts of the research community, in this study we introduce COVID-Net, a deep convolutional neural network design tailored for the detection of COVID-19 cases from chest X-ray (CXR) images that is open source and available to the general public. Furthermore, we investigate how COVID-Net makes predictions using an explainability method in an attempt to not only gain deeper insights into critical factors associated with COVID cases, which can aid clinicians in improved screening, but also audit COVID-Net in a responsible and transparent manner to validate that it is making decisions based on relevant information from the CXR images. Motivated by the urgent need to develop solutions to aid in the fight against the COvID-19 pandemic and inspired by the open source and open access efforts by the research community, this study introduces COVID-Net, a deep convolutional neural network design tailored for the detection of COVID-19 cases from CXR images that is open source and available to the general public.	./cache/cord-189307-qb0s06tl.txt	./txt/cord-189307-qb0s06tl.txt