A Medical Expert System for Tropical Diseases Diagnosis
DOI:
https://doi.org/10.26438/ijcse/v7i7.386390Keywords:
Expert system, fuzzy logic, typhoid and malaria, tropical diseases, diagnosisAbstract
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.
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.
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