The Medico-Task 2018: Disease Detection in the Gastrointestinal Tract using Global Features and Deep Learning

Authors	V. Thambawita, D. Jha, M. Riegler, P. Halvorsen, H. L. Hammer, H. D. Johansen and D. Johansen
Title	The Medico-Task 2018: Disease Detection in the Gastrointestinal Tract using Global Features and Deep Learning
Afilliation	Machine Learning
Project(s)	Department of Holistic Systems
Status	Published
Publication Type	Proceedings, refereed
Year of Publication	2018
Conference Name	MediaEval 2018
Date Published	10/2018
Publisher	MediaEval
Place Published	Nice, France
Keywords	CNN, deep learning, Gastrointestinal Disease Detection, Global Features, Medico-Task 2018, Transfer Learning
Abstract	In this paper, we present our approach for the 2018 Medico Task classifying diseases in the gastrointestinal tract. We have proposed a system based on global features and deep neural networks. The best approach combines two neural networks and the reproducible experimental results signify the efficiency of the proposed model with an accuracy rate of 95.80%, a precision of 95.87%, and an F1-score of 95.80%.
Citation Key	26205

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