Application of Expert System for Diagnosis of Monkeypox

Folake Akinbohun; Ambrose Akinbohun; Ebenezer Akinyemi Ajayi

doi:doi:10.11648/j.ajcst.20230603.11

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Application of Expert System for Diagnosis of Monkeypox

Folake Akinbohun, Ambrose Akinbohun, Ebenezer Akinyemi Ajayi

Published in American Journal of Computer Science and Technology (Volume 6, Issue 3)

Received: 10 August 2023 Accepted: 29 August 2023 Published: 13 September 2023

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Abstract

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.

Published in	American Journal of Computer Science and Technology (Volume 6, Issue 3)
DOI	10.11648/j.ajcst.20230603.11
Page(s)	96-101
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Expert System, Monkeypox, Inference Engine, Diagnosis

References

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[2]	Nolen, (2015) Monkeypox in a Traveler Returning from Nigeria—Dallas, Texas, July 2021. MMWR. Morb. Mortal.
[3]	Reynolds, M.; McCollum, A.; Nguete, B.; ShongoLushima, R.; Petersen, B (2013). Improving the Care and Treatment of Monkeypox Patients in Low-Resource Settings: Applying Evidence from Contemporary Biomedical and Smallpox Biodefense Research. Viruses 2013, 9, 380.
[4]	Cohen (2022). Data Models, Database Languages and Database Management System. Adison-Wesley Publication Company.
[5]	Popoola S. O. (2000). Expect system textbook, in Nigeria: Article on expert system Dictionary, 08/08/2009.
[6]	Omonyi A. S, (2013). Artificial Thinking, A tool for Effective Counseling. Journal of Counseling and Communication. (Counseling Association of Nigeria, Anambra State Chapter).
[7]	Huhn, G. D.; Holman, R. C.; Damon, I. K (2005). Clinical Manifestations of Human Monkeypox Influenced by Route of Infection. J. Infect. Dis. 2005, 194, 773–780.
[8]	WHO (2022). https://www.who.int/news-room/fact-sheets/detail/monkeypox
[9]	Sklenovská and Van, (2018). Use of JYNNEOS (Smallpox and Monkeypox Vaccine, Live, Nonreplicating) for Preexposure Vaccination of Persons at Risk for Occupational Exposure to Orthopoxviruses: Recommendations of the Advisory Committee on Immunization Practices—United States, 2018. MMWR. Morb. Mortal. Wkly. Rep. 2018, 71, 734–742.
[10]	ECDC (2022). Monkeypox Multi-Country Outbreak. Available online: https://www.ecdc.europa.eu/en/monkeypox-outbreak (accessed on 7 August 2022).
[11]	Bunge A., Ward M, Mark I (2022) Improving the Care and Treatment of Monkeypox Patients in Low-Resource Settings: Applying Evidence from Contemporary Biomedical and Smallpox Biodefense Research.
[12]	CDC, Monkeypox (2022): Signs and Symptoms. Available online: https://www.cdc.gov/poxvirus/monkeypox/symptoms.html (accessed on 7 August 2022).
[13]	Boghuma K. Titanji, Bryan Tegomoh, SamanNematollahi, Michael Konomos, and Prathit A. Kulkarni (2022). Monkeypox: A Contemporary Review for Healthcare Professionals. Open Forum Infectious Diseases.
[14]	Lum, F. M., Torres-Ruesta, A., Tay, M. Z. Lye, D. C., Renia, Laurent and Ng, Lisa F. P. (2022). Monkeypox: disease epidemiology, host immunity and clinical interventions. Nat Rev Immunol22, 597–613 (2022). https://doi.org/10.1038/s41577-022-00775-4
[15]	Amenu, O. and Assefa, A. (2022): Developing Expert System for Diagnosis and Treatment of Monkey Pox Outbreak. Journalhealthcare treatment development. Vol: 02, No. 04. http://journal.hmjournals.com/index.php/JHTD
[16]	Tom, J. J. and Anebo, N. P. (2018). A Neuro-Fussy Based Model for Diagnosis of Monkeypox Diseases. International Journal of Computer Science Trends and Technology (IJCST) – Volume 6 (2). https://www.researchgate.net/publication/325023546

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APA Style

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

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ACS Style

Folake Akinbohun; Ambrose Akinbohun; Ebenezer Akinyemi Ajayi. Application of Expert System for Diagnosis of Monkeypox. Am. J. Comput. Sci. Technol. 2023, 6(3), 96-101. doi: 10.11648/j.ajcst.20230603.11

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AMA Style

Folake Akinbohun, Ambrose Akinbohun, Ebenezer Akinyemi Ajayi. Application of Expert System for Diagnosis of Monkeypox. Am J Comput Sci Technol. 2023;6(3):96-101. doi: 10.11648/j.ajcst.20230603.11

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@article{10.11648/j.ajcst.20230603.11,
  author = {Folake Akinbohun and Ambrose Akinbohun and Ebenezer Akinyemi Ajayi},
  title = {Application of Expert System for Diagnosis of Monkeypox},
  journal = {American Journal of Computer Science and Technology},
  volume = {6},
  number = {3},
  pages = {96-101},
  doi = {10.11648/j.ajcst.20230603.11},
  url = {https://doi.org/10.11648/j.ajcst.20230603.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajcst.20230603.11},
  abstract = {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.},
 year = {2023}
}

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TY - JOUR
T1 - Application of Expert System for Diagnosis of Monkeypox
AU - Folake Akinbohun
AU - Ambrose Akinbohun
AU - Ebenezer Akinyemi Ajayi
Y1 - 2023/09/13
PY - 2023
N1 - https://doi.org/10.11648/j.ajcst.20230603.11
DO - 10.11648/j.ajcst.20230603.11
T2 - American Journal of Computer Science and Technology
JF - American Journal of Computer Science and Technology
JO - American Journal of Computer Science and Technology
SP - 96
EP - 101
PB - Science Publishing Group
SN - 2640-012X
UR - https://doi.org/10.11648/j.ajcst.20230603.11
AB - 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.
VL - 6
IS - 3
ER -

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Author Information

Folake Akinbohun

Department of Computer Science, Rufus Giwa Polytechnic, Owo, Nigeria
Ambrose Akinbohun

Department of ENT, Head and Neck Surgery, Prince Mishari Bin Saud Hospital, Baljurashi, Al Baha, Saudi Arabia
Ebenezer Akinyemi Ajayi

Department of Computer Science, Kebbi State Polytechnic, Dakingari, Nigeria

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APA Style

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

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ACS Style

Folake Akinbohun; Ambrose Akinbohun; Ebenezer Akinyemi Ajayi. Application of Expert System for Diagnosis of Monkeypox. Am. J. Comput. Sci. Technol. 2023, 6(3), 96-101. doi: 10.11648/j.ajcst.20230603.11

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AMA Style

Folake Akinbohun, Ambrose Akinbohun, Ebenezer Akinyemi Ajayi. Application of Expert System for Diagnosis of Monkeypox. Am J Comput Sci Technol. 2023;6(3):96-101. doi: 10.11648/j.ajcst.20230603.11

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@article{10.11648/j.ajcst.20230603.11,
  author = {Folake Akinbohun and Ambrose Akinbohun and Ebenezer Akinyemi Ajayi},
  title = {Application of Expert System for Diagnosis of Monkeypox},
  journal = {American Journal of Computer Science and Technology},
  volume = {6},
  number = {3},
  pages = {96-101},
  doi = {10.11648/j.ajcst.20230603.11},
  url = {https://doi.org/10.11648/j.ajcst.20230603.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajcst.20230603.11},
  abstract = {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.},
 year = {2023}
}

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