id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-032383-2dqpxumn	Shuja, Junaid	COVID-19 open source data sets: a comprehensive survey	2020-09-21		.txt	text/plain	16201	980	52	Our survey is motivated by the open source efforts that can be mainly categorized as (a) COVID-19 diagnosis from CT scans, X-ray images, and cough sounds, (b) COVID-19 case reporting, transmission estimation, and prognosis from epidemiological, demographic, and mobility data, (c) COVID-19 emotional and sentiment analysis from social media, and (d) knowledge-based discovery and semantic analysis from the collection of scholarly articles covering COVID-19. Automated CT scan based COVID-19 detection techniques work with training the learning model on existing CT scan data sets that contain labeled images of COVID-19 positive and normal cases. Triggered by this challenge limiting the adoption of AI/ML-powered COVID-19 diagnosis, forecasting, and mitigation, we make the first effort in surveying research works based on open source data sets concerning COVID-19 pandemic. The authors enlist the application of deep and transfer learning on their extracted data set for identification of COVID-19 while utilizing motivation from earlier studies that learned the type of pneumonia from similar images [47] .	./cache/cord-032383-2dqpxumn.txt	./txt/cord-032383-2dqpxumn.txt