id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-356271-k4ux9yey	Sai Thejeshwar, S.	Precise Prediction of COVID-19 in Chest X-Ray Images Using KE Sieve Algorithm	2020-08-14		.txt	text/plain	2699	184	66	The advancements in the area of machine learning and pattern recognition has resulted in intelligent systems that analyze CT Scans or X-ray images and classify between pneumonia and normal patients. This paper proposes KE Sieve Neural Network architecture, which helps in the rapid diagnosis of COVID-19 using chest X-ray images. So, in this study, we propose an AI-based pattern recognition system using the KE Sieve Neural Network model [1] [2] for the detection of coronavirus infected patients, pneumonia and healthy patients using chest X-ray radiographs. [25] , proposed a classification model that classifies COVID-19 from viral pneumonia and healthy cases using pulmonary CT images using deep learning techniques. Though the number of COVID-19 images available is too small, it had no effect on the model as a whole as transfer learning-based feature extraction is implemented and SNN [1] mathematically could separate each data point. A deep learning algorithm using CT images to screen for CoronaVirus Disease (COVID-19)	./cache/cord-356271-k4ux9yey.txt	./txt/cord-356271-k4ux9yey.txt