  Viral hepatitis is the regularly found health problem throughout the world
among other easily transmitted diseases, such as tuberculosis, human immune
virus, malaria and so on. Among all hepatitis viruses, the uppermost numbers of
deaths are result from the long-lasting hepatitis C infection or long-lasting
hepatitis B. In order to develop this system, the knowledge is acquired using
both structured and semi-structured interviews from internists of St.Paul
Hospital. Once the knowledge is acquired, it is modeled and represented using
rule based reasoning techniques. Both forward and backward chaining is used to
infer the rules and provide appropriate advices in the developed expert system.
For the purpose of developing the prototype expert system SWI-prolog editor
also used. The proposed system has the ability to adapt with dynamic knowledge
by generalizing rules and discover new rules through learning the newly arrived
knowledge from domain experts adaptively without any help from the knowledge
engineer.
  Keywords: Expert System, Diagnosis and Management of Viral Hepatitis,
Adaptive Learning, Discovery and Generalization Mechanism
