Abstract—The health of population, which is based primarily on the result of medical research, has a strong impact upon all human activities. Among the most important medical aspects are considered the good interpretation of data and setting the diagnosis. But medical decision making becomes a very hard activity because the human experts, who have to make decisions, can hardly process the huge amounts of data. So they need a tool that should be able to help them to make a good decision. There are a lot of tools which try to reduce the risk of error apparition in medical life. Diagnosis has a very important role here. It is the first step from a set of therapeutic actions; an error at this level can have dramatic consequences. The presence of technology in diagnosis phase is welcome because of its advantages: pragmatism, repeatability, efficiency, immunity toward perturbation factors that are specific to human beings (fatigue, stress, diminished attention). The technology doesn’t replace human experts in this point of medical assistance; it only tries to help them, implementing systems that are able to select or to generate data which are relevant. In medicine, diagnosis is "the recognition of a disease or stipulation by its apparent signs and symptoms" or "the analysis of underlying physiological, Biochemical cause(s) ". Hepatitis B including chronic liver disease is quite common in the world, which may cause damage to hepatocytes. The severity may range from healthy carrier to decompensated cirrhosis. In this paper we have described an intelligent system for the diagnosis of the Hepatitis B virus disease, as Hepatitis is one of the serious diseases which demands expensive 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 patient.
Index Terms—Medical Diagnosis; artificial intelligence, neural networks; hepatitis b; generalized regression neural network; hepatitis b virus (HBV); hepatitis b DNA.
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Cite: Dakshata Panchal and Seema Shah, "Artificial Intelligence Based Expert System For Hepatitis B Diagnosis," International Journal of Modeling and Optimization vol. 1, no. 4, pp. 362-366, 2011.
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