Open Access   Article Go Back

A Medical Expert System for Tropical Diseases Diagnosis

N.A. Ibiobu1 , N.D. Nwiabu2

Section:Research Paper, Product Type: Journal Paper
Volume-7 , Issue-7 , Page no. 386-390, Jul-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i7.386390

Online published on Jul 31, 2019

Copyright © N.A. Ibiobu, N.D. Nwiabu . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

View this paper at   Google Scholar | DPI Digital Library

How to Cite this Paper

  • IEEE Citation
  • MLA Citation
  • APA Citation
  • BibTex Citation
  • RIS Citation

IEEE Style Citation: N.A. Ibiobu, N.D. Nwiabu, “A Medical Expert System for Tropical Diseases Diagnosis,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.7, pp.386-390, 2019.

MLA Style Citation: N.A. Ibiobu, N.D. Nwiabu "A Medical Expert System for Tropical Diseases Diagnosis." International Journal of Computer Sciences and Engineering 7.7 (2019): 386-390.

APA Style Citation: N.A. Ibiobu, N.D. Nwiabu, (2019). A Medical Expert System for Tropical Diseases Diagnosis. International Journal of Computer Sciences and Engineering, 7(7), 386-390.

BibTex Style Citation:
@article{Ibiobu_2019,
author = {N.A. Ibiobu, N.D. Nwiabu},
title = {A Medical Expert System for Tropical Diseases Diagnosis},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {7 2019},
volume = {7},
Issue = {7},
month = {7},
year = {2019},
issn = {2347-2693},
pages = {386-390},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=4775},
doi = {https://doi.org/10.26438/ijcse/v7i7.386390}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i7.386390}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=4775
TI - A Medical Expert System for Tropical Diseases Diagnosis
T2 - International Journal of Computer Sciences and Engineering
AU - N.A. Ibiobu, N.D. Nwiabu
PY - 2019
DA - 2019/07/31
PB - IJCSE, Indore, INDIA
SP - 386-390
IS - 7
VL - 7
SN - 2347-2693
ER -

VIEWS PDF XML
312 281 downloads 157 downloads
  
  
           

Abstract

In Nigeria, tropical diseases such as Malaria and Typhoid are prevalent because of insects such as mosquitoes and flies, which are the common carriers of these diseases. Therefore, there is need for an expert system to help the inadequacy of the medical personnel in the diagnosis of these diseases. This paper presents the design of an expert system that aims at providing the patient with background for suitable diagnosis and treatments (Especially typhoid and malaria diseases). The system is able to give appropriate diagnosis and treatment for two diseases namely; typhoid and malaria. Fuzzy logic type 2 has proved to be the remarkable tool for building intelligent decision making for approximate reasoning that can appropriately handle both the uncertainties and imprecisions. The proposed methodology is composed of four stages: the first stage is receiving the symptoms from the patient, second stage, it uses information from the patient to make some analysis and investigation to improve correct decision in the diagnosis and the third stage, is performing diagnosis on patient according to information supplied by the patient (symptoms, analysis and investigation). The system was able to diagnose tropical diseases by the different symptoms using the fuzzy logic rule. The need to arrive at the most accurate medical diagnosis in a timely manner that reduces further complications is the main outcome of the system.

Key-Words / Index Term

Expert system, fuzzy logic, typhoid and malaria, tropical diseases, diagnosis

References

[1]. Bruce, Varun Chadha2, Chamandeep Maini, “A Review of Development and Applications of Expert System”, International Journal of Advanced Research in Computer Science and Software Engineering Vol.10, Issue.15, pp.319-325, 2015.
[2]. Jackson W, Heist RS, Liu G, et al. “Circulating 25-hydroxyvitamin D levels predict survival in early-stage non-small-cell lung cancer patients”, J Clinoncol; Vol.25, Issue.43, pp.479–485, 2000.
[3]. Feigenbaum Wells CK, Lee CH, Howard DH, Feinstein AR, “Variability in radiologists’ interpretations of mammograms”, N Engl J Med, Vol.1, Issue.22, pp.1493-1499, 2014.
[4]. Edward, N., Doumpos, M., and Zopounidis, C., “Knowledge acquisition and representation for expert systems in the field of financial analysis”. Expert Systems with Applications, Vol.12 Issue.25, pp.247-262, 2004.
[5]. Angeli, C. "Diagnostic expert systems: From expert’s knowledge to real-time systems." Advanced knowledge based systems: Model, applications & research Vol.1 pp.50-73, 2010.
[6]. Hochreiter and Schmidhuber, “Expert Systems Advances In Education”, NCCI National Conference On Computational Instrumentation CSIO Chandigarh 1999.
[7]. Jefferson D., & Negru, V., “An extensible environment for expert system development. In Knowledge-Based Intelligent Information and Engineering Systems”, Vol.45, Issue.72, pp.1016–1022, 2013.
[8]. Sushil, S. S., Sushil S., and Ali, M. S., "Fuzzy expert systems (FES) for medical diagnosis." International Journal of Computer Applications Vol.63, Issue.11, 2013.
[9]. Prihatini, P. M. and I. Ketut, G. D. P., "Fuzzy knowledge-based system with uncertainty for tropical infectious disease diagnosis.", International Journal of Computer Science Issues (IJCSI), Vol.9, Issue.4, pp.157, 2012.
[10]. Shortlife, B. G., and Shortliffe, E. H. “Rule-based expert systems: The MYCIN experiments of the Stanford Heuristic Programming.” Reading, MA: Addison-Wesley Vol.6 Vol.10, pp.34-60, 2014.
[11]. Pereira DC, Ramos RP, do Nascimento MZ., “Segmentation and detection of breast cancer in mammograms combining wavelet analysis and genetic algorithm.” Computer Methods Programs Biomed Apr, Vol.114, Issue.1, pp.88-101, 2014.
[12]. Denzin S. Abu Naser, Abu Zaiter A. Ola, “An Expert System for Diagnosing Eye Diseases Using CLIPS”, Journal of Theoretical and Applied Information Technology, Vol.15, Issue.25, pp.923-930, 2014.
[13]. Djam, X. Y., Wajiga, G. M., Kimbi, Y. H. and Blamah. N. V., “A fuzzy expert system for the management of malaria." 2011.
[14]. Iliff, E. C. and Calif, L. J., Computerized medical diagnostic and treatment advice system including list based processing, United States Patent, pp.1-38, 1999.