Data Mining and Machine Learning Algorithms Using <i>IL28B</i> Genotype and Biochemical Markers Best Predicted Advanced Liver Fibrosis in Chronic Hepatitis C-Reference-Cited by-同舟云学术

Data Mining and Machine Learning Algorithms Using IL28B Genotype and Biochemical Markers Best Predicted Advanced Liver Fibrosis in Chronic Hepatitis C

Published:2018 Issue:1 Volume:71 Page:51-57
ISSN:1344-6304
Container-title:Japanese Journal of Infectious Diseases
language:en
Short-container-title:Jpn J Infect Dis

Author:

Shousha Hend Ibrahim¹,Awad Abubakr Hussein²,Omran Dalia Abdelhamid¹,Elnegouly Mayada Mohamed¹,Mabrouk Mahasen¹

Affiliation:

1. Endemic Medicine Department, Faculty of Medicine, Cairo University

2. Computer Science Department, Faculty of Computers and Information, Cairo University

Publisher

Editorial Committee of Japanese Journal of Infectious Diseases, National Institute of Infectious Dis

Subject

Infectious Diseases,Microbiology (medical),General Medicine

Link

https://www.jstage.jst.go.jp/article/yoken/71/1/71_JJID.2017.089/_pdf

Reference47 articles.

1. 1. De Minicis S, Marzioni M, Saccomanno S, et al. Cellular and molecular mechanisms of hepatic fibrogenesis leading to liver cancer. Transl Gastrointest Cancer. 2012;1:88-94.

2. 2. Eslam M, Hashem AM, Leung R, et al. Interferon-λ rs12979860 genotype and liver fibrosis in viral and non-viral chronic liver disease. Nat Commun. 2015;6:6422.

3. 3. Waked I, Doss W, El-Sayed MH, et al. The current and future disease burden of chronic hepatitis C virus infection in Egypt. Arab J of Gastroentrol. 2014;15:45-52.

4. 4. Friedman SL. Mechanisms of hepatic fibrogenesis. Gastroenterology. 2008;134:1655-69.

5. 5. Noureddin M, Wright EC, Alter HJ, et al. Association of IL28B genotype with fibrosis progression and clinical outcomes in patients with chronic hepatitis C: a longitudinal analysis. Hepatology. 2013;58:1548-57.

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