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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.
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Informazioni sull'autore
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.
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Machine Learning for Predicting Hepatitis C Virus Therapy Outcomes
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LAP LAMBERT Academic Publishing Mrz 2017, 2017
ISBN 10: 3330059648
ISBN 13: 9783330059641
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 120 pp. Englisch. Codice articolo 9783330059641
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Machine Learning for Predicting Hepatitis C Virus Therapy Outcomes: HCV in Egypt
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Machine Learning for Predicting Hepatitis C Virus Therapy Outcomes
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Said MarwaMarwa 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 research. Codice articolo 151235379
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Machine Learning for Predicting Hepatitis C Virus Therapy Outcomes: HCV in Egypt
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ISBN 13: 9783330059641
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Machine Learning for Predicting Hepatitis C Virus Therapy Outcomes
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LAP LAMBERT Academic Publishing Mär 2017, 2017
ISBN 10: 3330059648
ISBN 13: 9783330059641
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 120 pp. Englisch. Codice articolo 9783330059641
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Machine Learning for Predicting Hepatitis C Virus Therapy Outcomes : HCV in Egypt
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LAP LAMBERT Academic Publishing, 2017
ISBN 10: 3330059648
ISBN 13: 9783330059641
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Da: AHA-BUCH GmbH, Einbeck, Germania
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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. Codice articolo 9783330059641
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Machine Learning for Predicting Hepatitis C Virus Therapy Outcomes: HCV in Egypt
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ISBN 13: 9783330059641
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Paperback. Condizione: Brand New. 120 pages. 8.66x5.91x0.28 inches. In Stock. Codice articolo __3330059648
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