Abstract: Hepatitis C virus (HCV) is a major cause of chronic liver disease, end stage liver disease and liver cancer in Egypt. Genotype 4 is the prevalent genotype in Egypt and has recently spread to Southern Europe particularly France, Italy, Greece and Spain. Recently, new direct acting antivirals (DAAs) have caused a revolution in HCV therapy with response rates approaching 100%. Despite the diversity of DAAs, treatment of chronic hepatitis C genotype 4 has not yet been optimized. The aim of this study is to build a framework to predict the response of chronic HCV genotype 4 patients to various DAAs by applying Data Mining Techniques (DMT) on clinical information. The framework consists of three phases which are data preprocessing phase to prepare the data before applying the DMT; DM phase to apply DMT, evaluation phase to evaluate the performance and accuracy of the built prediction model using a data mining evaluation technique. The experimental results showed that the model obtained acceptable results.

Mohammed A.Farahat, Khaled A.Bahnasy, A. Abdo, Sanaa M.Kamal, Samar K. Kassim and Ahmed Sharaf Eldin, “Response Prediction for Chronic HCV Genotype 4 Patients to DAAs” International Journal of Advanced Computer Science and Applications(IJACSA), 7(12), 2016. http://dx.doi.org/10.14569/IJACSA.2016.071223

@article{A.Farahat2016,
title = {Response Prediction for Chronic HCV Genotype 4 Patients to DAAs},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2016.071223},
url = {http://dx.doi.org/10.14569/IJACSA.2016.071223},
year = {2016},
publisher = {The Science and Information Organization},
volume = {7},
number = {12},
author = {Mohammed A.Farahat and Khaled A.Bahnasy and A. Abdo and Sanaa M.Kamal and Samar K. Kassim and Ahmed Sharaf Eldin}
}