id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-028786-400vglzm	Oloko-Oba, Mustapha	Diagnosing Tuberculosis Using Deep Convolutional Neural Network	2020-06-05		.txt	text/plain	2438	118	44	We propose a Computer-Aided Detection model using Deep Convolutional Neural Networks to automatically detect TB from Montgomery County (MC) Tuberculosis radiographs. As a result, to profer solution to the issue of limited or lack of expert radiologist and misdiagnosis of CXR, we propose a Deep Convolutional Neural Networks (CNN) model that will automatically diagnose large numbers of CXR at a time for TB manifestation in developing regions where TB is most prevalent. A model based on Deep Convolutional Neural Network (CNN) structure has been proposed in this work for the detection and classification of Tuberculosis. Presented in this paper is a model that aids early detection of Tuberculosis using CNN structure to automatically extract distinctive features from chest radiographs and classify them into normal and abnormal categories. TX-CNN: detecting tuberculosis in chest X-ray images using convolutional neural network	./cache/cord-028786-400vglzm.txt	./txt/cord-028786-400vglzm.txt