The development of a rule-based system for the diagnosis of candidiasis

Authors

  • Idongesit Efaemiode E Department of Computer Science, University of Calabar, Calabar, Cross River State, Nigeria
  • Udeze LC Department of Computer Science, University of Calabar, Calabar, Cross River State, Nigeria
  • Anuonye C Department of Computer Science, University of Calabar, Calabar, Cross River State, Nigeria
  • Okon U Department of Computer Science, University of Calabar, Calabar, Cross River State, Nigeria

Keywords:

Candidiasis, Rule-based system, Expert system, Diagnosis

Abstract

Candidiasis is one of the most common opportunistic fungal infections in existence. Globally, about 75% of women suffer from at least one episode of vulvovaginal candidiasis (VVC) annually. The nature of genital candidiasis infections, which includes vaginal and balanitis (inflammation of the glans penis) often hinders patients from seeking appropriate medical assistance in formal health facilities because these patients usually feel shy to engage experts. We developed a Web-based Expert System that provides a self-administered diagnosis of this condition. The system provides a diagnosis in conjunction with laboratory tests verification before treatment advice and remedial measures are recommended. Requirement gathering and specification were carried out through informal interviews and interactive sessions with health care providers, visitation to the laboratory and review of relevant literature on candidiasis infections. Simple production rules, as well as coded questions and answers, were employed for inferences. Valid and reliable inferences were made regardless of the Candidiasis scenario cases used in testing the system. Fifty (50) persons were tested and an average of 12% tested positive to the five (5) various types of Candidiasis. Treatment was recommended for such patients. The system could serve as initial diagnosis support for candidiasis.

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Published

2024-02-26

How to Cite

Idongesit Efaemiode, E., Udeze, L. C., Anuonye, C., & Okon, U. (2024). The development of a rule-based system for the diagnosis of candidiasis. COMPUSOFT: An International Journal of Advanced Computer Technology, 9(09), 3848–3855. Retrieved from https://ijact.in/index.php/j/article/view/591

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Original Research Article