Fuzzy Supervised Neural Training Algorithm for Varied Diabetes Recognition
DOI:
https://doi.org/10.14738/jbemi.15.403Keywords:
Supervised-Neural-Network, Fuzzy set, Fuzzy Logic, AlgorithmAbstract
Diabetes is a metabolic disorder associated with Blood Glucose Level. Most of the approaches applied in diagnosis are subjective in nature at best and tied toward Type I and Type II diabetes recognition, with none geared toward form of diabetes recognition. Fuzzy Supervised Neural Network Training Algorithm has been designed and implemented with Matrix Laboratory (MATLAB) and Hypertext Preprocessor as the simulation language. This paper demonstrates the practical application of algorithm techniques in medical diagnosis in determining patient’s status.
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