Diabetes is a chronic disorder caused by elevated glucose within the blood stream. The predominant indicator of diabetes include a glucose level of more 125mg/dl in addition to frequent thirst, unusual thirst, extreme fatigue blurred vision and frequent infection. Existing approach for the recognition of diabetes are to two classes (Type I and Type II) in addition to their subjective approach. This research paper proposed an objective approach utilizing soft-computing techniques for the recognition of five class of diabetes.

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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.