Predictive Model for Likelihood of Survival of Sickle-Cell Anaemia (SCA) Among Peadiatric Patients Using Fuzzy Logic
DOI:
https://doi.org/10.14738/tnc.31.842Keywords:
fuzzy logic, prediction model, sickle-cell disease, likelihoodAbstract
A fuzzy logic-based system has been applied to a number of cases in medicine especially in the area of the development of diagnostic systems and has been discovered to produce accurate results. In this paper, a fuzzy logic-based system is presented which is used to simulate a prediction model for determining the likelihood of Sickle Cell Anemia (SCA) in individuals given a 3-tuple record containing the level of fetal haemoglobin, genotype and the degree of Anemia.
Knowledge was elicited from an expert at Federal Medical Centre, Owo, Ondo State, Nigeria and was used in developing the rule-base and simulated the prediction model using the MATLAB software. The results of the fuzzification and defuzzification of variables, inference engine definition and model testing was also presented and showed that the fuzzy logic based model will be very useful in the prediction of the likelihood of Sickle Cell Anemia (SCA) among Nigerian patients.
References
. Malowany, J. I., Butany, J. (2012). Pathology of sickle cell disease. Seminars in Diagnostic Pathology, 29(1), pg. 49-55.
. Mishra, N., Jha, P. (2014) Framing Fuzzy Rules using Mamadani Model for Effective Sickle Cell Diagnosis. International Journal of Engineering Sciences and Research Technology. 3(6), June 2014, pg. 389-396, ISSN: 2277-9655.
. Obeagu, E. I., Ogbuabor, B. N., Ikechukwu, O. A., Chude, C. N. (2014) Haematological parameters among sickle cell anemia patients’ state and haemoglobin genotype AA individuals at Michael Okpara University of Agriculture, Umudike, Abia State, Nigeria. International Journal of Current Microbiology and Applied Sciences; 3(3), pg. 1000 – 1005, ISSN: 2319-7706.
. Omoti, C. E.2005.Haematological Values in Sickle Cell Anaemia in Steady State and During Vaso-occlusive Crisis in Benin City, Nigeria Annals of African Medicine, 42, pg.62-67.
. Pauling, L., Itano, H.A., Singer, S. J., Wells, I. C. (1949). Sickle Cell Anaemia: a Molecular Disease. Journal of Science 110, pg. 543-548.
. Ukpong, E. (1992) Current Concepts in the Management of Sickle Cell Disorders. Kraft Books, Ibadan.
. Wellems, T. E., Hayton, K., Fairhurst, R. M. (2009). The impact of malaria parasitism: from corpuscles to communities. Journal of Clinical Investment; 119 (9), pg. 496-505.
. Aramideh, J., Jelodar, H. (2014) Application of Fuzzy logic for presentation of an expert system to diagnose anemia. Indian Journal of Science and Technology, 7(7), pg. 933-938, July 2014. ISSN: 0974-6846.
. Sayyahi, H. (2008). An application of fuzzy case based reasoning for poison classification. Unpublished Masters in Information Technology Thesis. University of Malaysia.
. Goyal, D. (2006) Disease Diagnostic System using LabVIEW. Unpublished Masters of Engineering in Electronics Instrumentation and Control Engineering Thesis. Thapar Institute of Engineering and Technology, Deemed University, Punjab.
