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Standardising Neural Networks and Fuzzy Logic Diagnostics Results of Hepatitis Patients

O.U. Obot, S.S. Udoh


Fuzzy logic is a known Soft Computing technique for managing imprecise, vague and ambiguous data and uncertain information. Artificial Neural Network is known to generalise from the data it has not encountered before. These attributes of data were found prevalent in information gathered from hepatitis patients. The information given from hepatitis patients are so imprecise as the patient could not explain exactly how they feel, neither were the doctors able to decipher exactly the results of their examination of the patients. These led to the applications of the two techniques in evaluating the diagnosis of hepatitis of 30 patients. The results obtained indicate a strong correlation necessitating the use of a standard scale function to standardise and average the results. The output of this is deemed as the final diagnostic results of each of the 30 patients’ data used for the study. The degree to which a patient suffers from hepatitis reported in the standardised diagnostic results strengthens the results of this study over similar previous results reviewed in the literatures.


Fuzzy logic, soft computing, artificial neural network, expert system.

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