id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-259481-og7n82fl	Zhang, Hai-tao	Automated detection and quantification of COVID-19 pneumonia: CT imaging analysis by a deep learning-based software	2020-07-14		.txt	text/plain	2915	155	52	Radiological examinations, especially thin slice chest Computed tomography (CT) scans, play an important role in identifying the early phase of lung infection, monitoring disease progression and guiding clinical decision making for COVID-19 patients [5, 7, 8] . In the present study, the uAI Intelligent Assistant Analysis System, a deep learning-based software, was used to automatically extract and analyse regions suspected to be infected with the virus. The uAI Intelligent Assistant Analysis System, a deep learningbased software, was specifically developed by United Imaging Medical Technology Company Limited (Shanghai, China) for COVID-19 assessment. In this study, we analysed the CT scans of 2460 COVID-19 patients using the uAI Intelligent Assistant Analysis System. The ability of the uAI Intelligent Assistant Analysis to quickly and accurately localize and quantify infection regions from CT scans will not only aid in the diagnosis of COVID-19, but also aid in assessing the disease to help guide physicians in their treatment plans.	./cache/cord-259481-og7n82fl.txt	./txt/cord-259481-og7n82fl.txt