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Diagnosing Oral Ulcers with Bayes Model

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Innovations in Bio-Inspired Computing and Applications (IBICA 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 939))

Abstract

An oral ulcer is considered an ulcer that occurs on the mucous membrane of the oral cavity. Its treatment however poses a serious challenge as experts in this area of family health care are rare. In order to affirm this claim, questionnaire was designed and distributed to get up-to-date information concerning the ailment, particularly its treatment, causes, and solutions among others. An expert system seeks to mimic the functions and capabilities of a real life expert. This means that just as the expert is domain specific, the expert system as well is domain specific. It consists of a user interface, a knowledge-base, a fact-base, and an inference engine; all working together to mimic an expert. Bayesian inference was used in this work to factor in probability as it is well known that the fact that one is experiencing the symptoms of a disease does not absolutely mean that one has that disease. The domain of this expert system is oral ulcer and it focuses on four common oral ulcers which include: Cold sores, Gingivostomatitis, Herpangina as well as Neutropenia. The application which was designed with Object-Oriented Analysis and Design methodology was implemented with java programming language, provided on the Netbeans 8.0.2 IDE.

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Acknowledgments

We acknowledge the support and sponsorship provided by Covenant University through the Centre for Research, Innovation and Discovery (CUCRID).

Author information

Authors and Affiliations

  1. North-West University, Vaal Triangle Campus, Vanderbijlpark, South Africa

    Nureni Ayofe Azeez, Samuel O. Oyeniran & Charles Van der Vyver

  2. Covenant University, Ota, Nigeria

    Sanjay Misra

  3. Vishwakarma Skill University Gurugram, Gurugram, India

    Ravin Ahuja

  4. Kaunas University of Technology, Kaunas, Lithuania

    Robertas Damasevicius & Rytis Maskeliunas

Authors
  1. Nureni Ayofe Azeez
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  2. Samuel O. Oyeniran
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  3. Charles Van der Vyver
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  4. Sanjay Misra
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  5. Ravin Ahuja
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  6. Robertas Damasevicius
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  7. Rytis Maskeliunas
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Corresponding author

Correspondence to Sanjay Misra .

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Editors and Affiliations

  1. Machine Intelligence Research Labs, Auburn, WA, USA

    Ajith Abraham

  2. Machine Intelligence Research Labs, Auburn, WA, USA

    Niketa Gandhi

  3. Department of Applied Science and Engineering, Indian Institute of Technology, Roorkee, India

    Millie Pant

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Azeez, N.A. et al. (2019). Diagnosing Oral Ulcers with Bayes Model. In: Abraham, A., Gandhi, N., Pant, M. (eds) Innovations in Bio-Inspired Computing and Applications. IBICA 2018. Advances in Intelligent Systems and Computing, vol 939. Springer, Cham. https://doi.org/10.1007/978-3-030-16681-6_48

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