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2019 | OriginalPaper | Chapter

Computer Aided Diagnosis of Gastrointestinal Diseases Based on Iridology

Authors : Enrique V. Carrera, Jennifer Maya

Published in: Technology Trends

Publisher: Springer International Publishing

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Abstract

Gastrointestinal diseases are important causes of mortality and expenses around the world. Since conventional methods for diagnosing gastrointestinal problems are expensive and invasive, alternative medicine techniques emerge as a possibility for helping physicians in this type of diagnosis. Hence, this work proposes a computer aided diagnosis system based on iridology for early detection of gastrointestinal diseases. The proposed system employs image processing and machine learning algorithms to identify gastrointestinal disorders in iris images. The evaluation of the system uses 100 iris images showing a maximum accuracy of 96% and a predictive capacity of 99%. This work shows that alternative medicine techniques have potential for diagnosing problems associated to gastrointestinal disorders.

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Literature
1.
Daugman, J.: How iris recognition works. In: The Essential Guide to Image Processing, pp. 715–739. Elsevier (2009)
2.
Gonzalez, R.C., Eddins, S.L.: Digital Image Processing Using Matlab (2017)
3.
Haroon, D.: Python Machine Learning Case Studies: Five Case Studies for the Data Scientist, vol. 1. Apress, New York City (2017)
4.
National Institutes of Health and US Department of Health and Human Services: Opportunities and challenges in digestive diseases research: recommendations of the national commission on digestive diseases. National Institutes of Health, Bethesda, MD (2009)
5.
6.
Jensen, B.: Iridology Simplified. Book Publishing Company, Summertown (2012)
7.
Laganière, R.: OpenCV Computer Vision Application Programming Cookbook, vol. 2. Packt Publishing Ltd, Birmingham (2014)
8.
9.
Samant, P., Agarwal, R.: Diagnosis of diabetes using computer methods: soft computing methods for diabetes detection using iris. Power 651, 63915 (2017)
10.
Sivasankar, K., Sujaritha, M., Pasupathi, P., Muthukumar, S.: FCM based iris image analysis for tissue imbalance stage identification. In: Emerging Trends in Science, Engineering and Technology, pp. 210–215. IEEE (2012)
11.
Theodoridis, S., Pikrakis, A., Koutroumbas, K., Cavouras, D.: Introduction to Pattern Recognition: A Matlab Approach. Academic Press, Cambridge (2010)
12.
Van der Walt, S., et al.: Scikit-image: image processing in Python. PeerJ 2, e453 (2014)
13.
Wildes, R.P.: Iris recognition: an emerging biometric technology. Proc. IEEE 85(9), 1348–1363 (1997)
14.
Wilson, A.D.: Recent applications of electronic-nose technologies for the noninvasive early diagnosis of gastrointestinal diseases. In: Multidisciplinary Digital Publishing Institute Proceedings, vol. 2, p. 147 (2017)
15.
Wong, T.T.: Performance evaluation of classification algorithms by k-fold and leave-one-out cross validation. Pattern Recognit. 48(9), 2839–2846 (2015)
Metadata
Title
Computer Aided Diagnosis of Gastrointestinal Diseases Based on Iridology
Authors
Enrique V. Carrera
Jennifer Maya
Copyright Year
2019
Book
Technology Trends

Print ISBN: 978-3-030-05531-8

Electronic ISBN: 978-3-030-05532-5

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-3-030-05532-5_40

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