Knowledge Sharing Tool on Hepatitis B Virus (HBV) Disease and the Risk of Chronicity Rate Using Generalized Regression Neural Network

This paper proposes a framework for a Knowledge Sharing Tool on Hepatitis B (HBV) Risk of Chronicity Rate in Mubi north metropolis of Adamawa State as Hepatitis is one of the severe diseases which demands exclusive treatment and severe side effects can appear very often. The intelligent system consists of the Generalized Regression Neural Network which gives the result for whether the patient is Hepatitis B positive or not and the severity of the disease in the patient. Here the researchers also considered the Risk of Chronicity as related to age at primary infection stage in such categories as, neonates, children and adults with 150 diagnosis samples collected from five different health centers in Mubi metropolis. These patients were placed on monitoring/observation for a period of six months to study their migration from acute to chronic stage within the period. Simple descriptive statistics of percentage was used in the analysis of the collected samples and the result shows that 76.19 % of neonates are faced with risk of chronicity, 19.05 % of children are also faced with the risk of chronicity while 4.76 % of adults are faced with the risk of chronicity.