Prognosis Model of Hepatitis B Reactivation Using Decision Tree-Reference-Cited by-同舟云学术

Prognosis Model of Hepatitis B Reactivation Using Decision Tree

Published:2020-09-17 Issue: Volume: Page:371-376
ISSN:2524-7565
Container-title:Algorithms for Intelligent Systems
language:
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Author:

Atef Syed,Anand Vishal,Venkatesh Shruthi,Katey Tejaswini,Mohanchandra Kusuma

Publisher

Springer Singapore

Link

http://link.springer.com/content/pdf/10.1007/978-981-15-4936-6_40

Reference5 articles.

1. Wu, G. P., Wang, S., Huang, W., Liu, T. H., Yin, Y., & Liu, Y. H. (2016). Classification prognosis model of hepatitis B virus reactivation after radiotherapy in patients with primary liver carcinoma based on BP neural network. Intelligent Computer and Applications, 6, 43–47.

2. Yao, H., Gong, J. L., Li, L., & Wang, Y. (2014). Risk factors of hepatitis b virus reactivation induced by precise radiotherapy in patients with hepatic carcinoma. The Practical Journal of Cancer, 29, 675–677.

3. Shuai, W., Guan-peng, W., Wei, H., Tong-hai, L., Yong, Y., & Yi-hui, L. (2016). The predictive model of hepatitis B virus reactivation induced by precise radiotherapy in primary liver cancer. Journal of Electrical and Electronic Engineering, 4(2), 31–34.

4. Guan-peng, W., Shuai, W., Wei, H., Tong-hai, L., Yong, Y., & Yi-hui, L. (2016). Application of BP and RBF Neural network in classification prognosis of hepatitis B virus reactivation. Journal of Electrical and Electronic Engineering, 4(2), 35–39.

5. Wu, G., Liu, Y., Wang, S., Huang, W., Liu, T., & Yin, Y. (2016, August) The classification prognosis models of hepatitis b virus reactivation based on Bayes and support vector machine after feature extraction of genetic algorithm. In 2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD) (pp. 572–577). IEEE.