id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-286887-s8lvimt3	Nour, Majid	A Novel Medical Diagnosis model for COVID-19 infection detection based on Deep Features and Bayesian Optimization	2020-07-28		.txt	text/plain	3686	250	55	The proposed model is based on the convolution neural network (CNN) architecture and can automatically reveal discriminative features on chest X-ray images through its convolution with rich filter families, abstraction, and weight-sharing characteristics. study [5] , they used Chest Computed Tomography (CT) images and Deep Transfer Learning (DTL) method to detect COVID-19 and obtained a high diagnostic accuracy. proposed a novel hybrid method called the Fuzzy Color technique + deep learning models (MobileNetV2, SqueezeNet) with a Social Mimic optimization method to classify the COVID-19 cases and achieved high success rate in their work [6] . (2) The deep features extracted from deep layers of CNNs have been applied as the input to machine learning models to further improve COVID-19 infection detection. Only the number of samples in the COVID-19 class is increased by using the offline data augmentation approach, and then the proposed CNN model is trained and tested.	./cache/cord-286887-s8lvimt3.txt	./txt/cord-286887-s8lvimt3.txt