id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
bam-11571	Joni, Saeid Sadeghi; Gerami, Reza; Pashaei, Fakhereh; Ebrahiminik, Hojat; Karimi, Mahmood	Quantitative evaluation of CT scan images to determinate the prognosis of COVID-19 patient using deep learning	2023	9	.pdf	application/pdf	5602	350	56	 CT scan for prognosis of COVID-19 by deep learning Eur J Transl Myol 33 (3) 11571, 2023 doi: 10.4081/ejtm.2023.11571 - 1 - Quantitative evaluation of CT scan images to determinate the prognosis of COVID-19 patient using deep learning Saeid Sadeghi Joni (1), Reza Gerami (1), Fakhereh Pashaei (2), Hojat Ebrahiminik (3), Mahmood Karimi (4) (1) Department of Radiology, Faculty of medicine, Aja University of Medical Sciences, Tehran, Iran; (2) Radiation Sciences Research Center (RSRC), Aja University of Medical Sciences, Tehran, Iran; (3) Department of Interventional Radiology and Radiation Sciences Research Center, Furthermore, AI was found to be useful in identifying COVID-19 pneumonia of other origin using chest CT with good diagnostic accuracy as well as predicting COVID-19 respiratory problems.8	cache/bam-11571.pdf	txt/bam-11571.txt