id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-032657-1egdwe26	Gouda, Walaa	COVID-19 disease: CT Pneumonia Analysis prototype by using artificial intelligence, predicting the disease severity	2020-09-25		.txt	text/plain	4128	205	50	Groups B and C showed significantly increased number of involved lung segments and lobes, frequencies of consolidation, crazy-paving pattern, and air bronchogram. CT severity score was estimated for each one of the five lung lobes by calculating the dissemination of the chest manifestations (opacity), namely the ground-glass opacities (GGO), consolidation, crazy-paving pattern, septal thickening, and pulmonary fibrosis giving score (0-4) for 0, 25, 50, and ≥ 75% involvement, respectively, with the sum representing the total severity scores for the whole lung (0-20). In our study, qualitative chest findings such as consolidation, air bronchogram, septal thickening, lung fibrosis, and pleural effusion showed a significant difference between group A and other groups (B and C) with P value < 0.001, but it could not differentiate between groups B and C.	./cache/cord-032657-1egdwe26.txt	./txt/cord-032657-1egdwe26.txt