A Master’s Thesis on: Diagnosis and Treatment of Viral Hepatitis Liver Disease Employing Machine Learning Technology

On the grand event hall in College of Engineering, Al-Iraqia University, a master’s thesis was discussed by the researcher (Ibrahim Ismail Ahmed) entitled Diagnosis and treatment of viral liver disease using machine learning technology.

The message included knowing realistic data for symptoms of viral liver disease in addition to building an independent classification platform that can work without a need to link it to another system and use the (Random Forest, Decision Tree, Support Vector Machine) to classify people as healthy or sick with viral hepatitis using the (AWFS) system and a number of lowest of symptoms , a strong correlation between symptoms of patients and the diagnosis of hepatitis based on this research was determined.

The thesis aimed to improve the diagnosing hepatitis in its early stages, which reduces the acute effects on human life. It should be noted that RF gave the highest accuracy of diagnosing of the disease regardless of number of symptoms used compared to DT, SVM due to the use of AWFS, based on the importance of repeated presentation during the whole process .