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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Acknowledgments
Authors would like to thank Dr. Telmo De la Torre for helping us to diagnose gastrointestinal diseases in the iris images used in this work. This work was partially supported by the Universidad de las Fuerzas Armadas ESPE under Research Grant 2015-PIC-004.
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Carrera, E.V., Maya, J. (2019). Computer Aided Diagnosis of Gastrointestinal Diseases Based on Iridology. In: Botto-Tobar, M., Pizarro, G., Zúñiga-Prieto, M., D’Armas, M., Zúñiga Sánchez, M. (eds) Technology Trends. CITT 2018. Communications in Computer and Information Science, vol 895. Springer, Cham. https://doi.org/10.1007/978-3-030-05532-5_40
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DOI: https://doi.org/10.1007/978-3-030-05532-5_40
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