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Computer Aided Diagnosis of Gastrointestinal Diseases Based on Iridology

  • Enrique V. CarreraEmail author
  • Jennifer Maya
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 895)

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.

Keywords

Gastrointestinal diseases Iridology techniques Image processing Machine learning 

Notes

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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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Departamento de Eléctrica y ElectrónicaUniversidad de las Fuerzas Armadas ESPESangolquíEcuador

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