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1Department of Computer Science, Rufus Giwa Polytechnic, Owo, Nigeria
2Department of ENT, Head and Neck Surgery, Prince Mishari Bin Saud Hospital, Baljurashi, Al Baha, Saudi Arabia
3Department of Computer Science, Kebbi State Polytechnic, Dakingari, Nigeria
Monkeypox is a virus-borne disease that spreads from animals to humans and causes symptoms similar to those experienced in smallpox patients. The most important orthopoxvirus develops as Monkeypox. Natural hosts include vertebrates such as animals and humans, as well as arthropods. People can become infected with the Monkeypox virus by coming into touch with infected animals or humans (living or dead). An Expert System (ES) technique can be used to diagnose this condition. It (ES) is a computer program with a set of rules that evaluates data about a certain class or outcome. The increase rate of Monkeypox disease, limited or inadequate medical personnel in the local areas and inaccessibility to the medical facilities in getting medical services by the patients are the challenges; and these call for the design of the Expert System. This study is aimed to diagnose Monkeypox in order to complement the services of the medical personnel. The proposed system is based on Expert System thatconsists of User interface, Inference engine and Knowledge base. The signs and symptoms of Monkeypox disease are gathered from various Clinics and Hospitals, then built the Inference Engine where IF-THEN rules are domiciled to act intelligently on the symptoms and diagnose the degree of intensity of the disease (Monkeypox virus). The study is implemented using programming language tools: PHP, MySQL and Vue JS framework. This study could be deployed in the hospitals to complement the services of health workers especially where medical experts are not sufficient. This could also be used in a situation where patients are not having access to healthcare facilities to diagnose Monkeypox on time and early referral could be done on time to the appropriate healthcare centres.
Expert System, Monkeypox, Inference Engine, Diagnosis
Folake Akinbohun, Ambrose Akinbohun, Ebenezer Akinyemi Ajayi. (2023). Application of Expert System for Diagnosis of Monkeypox. American Journal of Computer Science and Technology, 6(3), 96-101. https://doi.org/10.11648/j.ajcst.20230603.11
Copyright © 2023 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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