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An Expert System For Hepatitis B Diagnosis Using Artificial Neural Networks

Author(s): Dakshata Panchal | Seema Shah

Journal: International Journal of Computer Applications
ISSN 0975-8887

Volume: icwet;
Issue: 11;
Date: 2012;
Original page

Keywords: Medical Diagnosis; Artificial Intelligence | Neural Networks; Hepatitis B; Generalized Regression Neural Networks; Hepatitis B virus(HBV); Hepatitis B DNA

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 medicine, diagnosis is "the recognition of a disease or stipulation by its apparent signs and symptoms" or "the analysis of the underlying physiological! Biochemical cause(s) of a disease or condition". An important issue in medical diagnosis is the risk stratification, which refers to the sorting of patients based on the severity of disease. In case the clinical problem lies beyond the physician's competence, the solution is to consult a specialist, however in common, expert opinion is either unavailable or not available in a timely fashion. The physician is left without adequate time to devote to each case and struggling to keep up with the newest developments in his field owing to our increasing expectations of the highest quality health care and the rapid_growth_of_ever_more_detailed_medical_knowledge. In this paper we have described an expert system for the diagnosis of the Hepatitis B virus disease, which consists of the generalized regression neural network. The main aim of the system is to classify the patient in two categories : Infected or Immune mentioning the causes and severity

Tango Jona
Tangokurs Rapperswil-Jona

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