Experimental study of fuzzy-rule based management of tropical diseases: case of malaria diagnosis.
The application of the conventional symbolic rules found in knowledge base technology to the management of a disease suffers from its inability to evaluate the degree of severity of a symptom and by extension the degree of the illness. Fuzzy logic technology provides a simple way to arrive at a definite conclusion from vague, ambiguous, imprecise and noisy data (as found in medical data) using linguistic variables that are not necessary precise. In order to achieve this, a study of a knowledge base system for the management of diseases was undertaken. The Root Sum Square of drawing inference was employed to infer the data from the rules developed. This resulted in the establishment of some degrees of influence on the diseases. Using malaria as a case study, a system that uses Visual Basic .Net development environment was developed and the results of the computations are presented in this research.
Obot
Okure U
OU
Dept of Mathematics, Statistics and Computer Science, University of Uyo, Nigeria. abatakure@yahoo.com
Uzoka
Faith-Michael E
FM
D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D017143:Fuzzy Logic; D006801:Humans; D008288:Malaria / Q000175:diagnosis*; D012720:Severity of Illness Index; D014330:Tropical Medicine; D014584:User-Computer Interface