A Knowledge Based System Design for the Diagnosis and Control of Ebola Virus Disease (EVD) Using GRNN

Authors

  • Sarjiyus. O  Department of Computer Science, Adamawa State University, P.M.B 25, Mubi, Nigeria

Keywords:

Intelligent, Diagnosis, GRNN, Reliability, Design.

Abstract

This research, an intelligent based system design for the diagnosis of Ebola Virus Disease (EVD) has presented an application of expert system for the diagnosis of Ebola Virus Disease with better performance, reliability and increased efficiency. The aim is to design an intelligent system using GRNN for the diagnosis of EVD. The EDSS is designed using Java platform (Netbeans 6.9.1), SQlite, and other tools such as UML Ucase diagrams, system flowchart etc, which are used to capture the basic functionalities needed for the design on the system needed to optimally actualize the overall objective of the new system design.

References

  1. Adeyeye P, Michael F, Damilare O, Ndubisi A, Segun K and Oluyemi R. (2014). Knowledge Attitude Practices of Nigerians on the EVD Survey Report.
  2. Amira R, and Delfim 0F.M. Torres. (2015). Modelling dynamics and optical control of Ebola Virus spread. 1, (2) 277-289.
  3. Ayithan N, Bradfute SB, Anthony SM, Stuthman KS, Bavari S, Bray M, Keiko O. Virus-like particles activate type I interferon pathways to facilitate post-exposure protection against Ebola virus infection. PLOS One. 2015;10(2):1-17. DOI:10.1371/journal.pone.0118345.
  4. Baize S, Leroy EM, Georges AJ, GeorgesCourbot, MC, Capron M, Bedjabaga I, Lansoud-Soukate J, Mavoungou E. (2014).Inflammatory responses in Ebola virusinfected patients. The Journal of Translational Immunology. 2002;128(1):163-168.
  5. Barry M, Traor´e FA, Sako FB, Kpamy DO, Bah EI, Poncin M, Keita S, Cisse M, Tour´e A. Ebola outbreak in Conakry, Guinea: Epidemiological, clinical, and outcome features. M´edecine et Maladies Infectieuses. 2014; 44: 491–494.
  6. Chippaux JP. Outbreaks of Ebola virus disease in Africa: The beginning of a tragic saga. Journal of Venomous Animals and Toxins including Tropical Diseases. 2014; 20:1-14.
  7. Davtyan M, Brown B, Folayan MO. Addressing Ebola-related stigma: Lessons learned from HIV/AIDS. Glob Health Action. 2014;7:26058.
  8. Infection, Prevention and Control Recommendations for Hospitalized Patients with Known or Suspected Ebola Virus Disease in U.S. Hospitals. Ebola Virus Diesease. Centers for Disease Control and Prevention; (2014) Available at http://www.cdc.gov/vhf/ebola/hcp/infectionprevention-and-controlrecommendations.html
  9. Katz LM, Tobian AA. Ebola virus disease, transmission risk to laboratory personnel, and pretransfusion testing. Transfusion. 2014; 54(12): 3247–3251.
  10. Koenig KL, Majestic C, Burns MJ. Ebola virus disease: Essential public health principles for clinicians. West J. Emerg. Med. 2014; 15(7):728–731.
  11. Kulkarni, S. G. (2004). Modeling and monitoring of batch processes using principal component analysis (PCA) assisted generalized regression neural networks (GRNN), Biochemical Engineering Journal, (18)3, 193-210.
  12. Legrand J, Graus RF, Boelle PY, Valleron AJ, Flahault A. (2007). Understanding the dynamics of Ebola epidemics. Epidemiol Infect. (135) 610-621.
  13. Li L, Guan J, Liang LJ, Lin C, Wu Z. Popular opinion leader intervention for HIV stigma reduction in health care settings. AIDS Educ Prev. 2013; 25(4):327–335.
  14. Mahesh, C., Kannan, E. & Saravanan, M. S. (2014). Generalized regression neural network based expert system for Hepatitis b diagnosis. Journal of computer science 4(10), 563-569.
  15. Marzi A, Ebihara H, Callison J, Groseth A, Williams KJ, Geisbert TW, Feldmann H. Vesicular stomatitis virus-based Ebola vaccines with improved cross-protective efficacy. Journal of Infectious Diseases. 2015; 212(2): 1066–1074.
  16. Nyenswah TG, Westercamp M, Kamali AA, Qin J, Zielinski-Gutierrez E, Amegashie F. Evidence for declining numbers of ebola cases - montserrado county, Liberia. MMWR Morb Mortal Wkly Rep. 2014;63(46):1072–1076.
  17. Osungbade KO, Oni AA. Outbreaks of Ebola virus disease in the West African sub-region. Afr J. Med Sci. 2014;43(2):87–97.
  18. Pillai SK, Nyenswah T, Rouse E, Arwady MA, Forrester JD, Hunter JC. Centers for Disease Control and Prevention (CDC). Developing an incident management system to support Ebola response – Liberia. 2014;63(41):930–933.
  19. Sunday J, Kwanamu JA, Bakari AI. Computational approach for the solution of some electric circuit problems. Advances in Research. 2016; 7(5): 1-9.
  20. WHO. Ebola response roadmap situation report. who.int. (2014).

IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

Downloads

Published

2018-04-30

Issue

Volume 3, Issue 3, March-April-2018

Section

Research Articles

License

Copyright (c) IJSRCSEIT

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Sarjiyus. O, " A Knowledge Based System Design for the Diagnosis and Control of Ebola Virus Disease (EVD) Using GRNN, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 3, pp.2084-2095, March-April-2018.