Use Of Logic Functions In The Diagnosis Of Hepatitis Disease Through A Web-Based Expert System Design: A Different Approach

Hepatitis disease is one of the most important health problems in the world. It is estimated that 1.3 million people worldwide die each year from viral hepatitis, one of the most significant causes of hepatitis disease, and that one out of every three people in the world has been infected with the Hepatitis B virus (HBV). In this study, a Web-Based Medical Expert System (WBMES) was developed to diagnose hepatitis disease using logic functions. The system has been developed to raise the awareness of hepatitis disease – which negatively affects individual and community health, and hinders productivity – and increase the rates of early diagnosis and reduce the negative effects on individuals and the community. To do this, a truth table was created that included nine symptoms of hepatitis disease and 512 rules (2⁹ = 512). Within this scope, the 512 rules in the truth table were evaluated together with specialist doctors to create a rule base called the Medical Expert System (MES), and a web-interface was developed to access it. The system was evaluated using the Hepatitis Dataset obtained from the UCI Repository of Machine Learning Databases, and it was found that the system's evaluation success rate was 98.68%.