Machine Learning for Predicting Hepatitis C Virus Therapy Outcomes: HCV in Egypt - Softcover

Said, Marwa; El Hefnawi, Mahmoud; Abdalla, Mahmoud

Softcover

ISBN 10: 3330059648 ISBN 13: 9783330059641

Publisher: LAP LAMBERT Academic Publishing, 2017

Synopsis

Although the current scientific revolution and the great improving of the health care systems, hepatitis C virus (HCV) continues to be a major health risk in both developed and developing countries and is considered one of the most important causes of chronic liver disease. It accounts for about 15% of acute viral hepatitis, 60% to 70% of chronic hepatitis C(CHC) and up to 50% of cirrhosis, end-stage liver disease and liver cancer. An estimated 150-200 million people worldwide are infected with hepatitis C. Unfortunately,there are a few published simulation models related to HCV problem.All attempts depending on one mathematical model that describes the virologic infections published by Alan Perelson at 1999. After that, many researchers applied this model on studying hepatitis C dynamics. Comparatively higher rate of sustained virologic response(SVR)which defined as undetectable HCV ribonucleic acid(RNA)and end of treatment response(ETR) observed more pronounced in patients treated with pegylated interferon (Peg-IFN) and ribavirin(RBV) than standard combination treatment. Patients with CHC often stop subsuming the treatment because of the high cost and related unfavorable effects.

About this title

About the Author

Marwa S. Hassan, M.SC: studied in bioinformatics team at national research center and Zagazig University, interested in the issues of my country, headed by virus C problem which is described in this book. Assistant researcher at the National Research Center, Cairo.

Edition details

• Publisher: LAP LAMBERT Academic Publishing
• Publication date: 2017
• Language: English
• ISBN 10: 3330059648
• ISBN 13: 9783330059641
• Binding: Paperback
• Number of pages: 120