Liver cancer prediction in a viral hepatitis cohort: A deep learning approach-Reference-Cited by-全球学者库

Liver cancer prediction in a viral hepatitis cohort: A deep learning approach

Published:2020-08-20 Issue:10 Volume:147 Page:2871-2878
ISSN:0020-7136
Container-title:International Journal of Cancer
language:en
Short-container-title:Int. J. Cancer

Author:

Phan Dinh‐Van¹²³^ORCID,Chan Chien‐Lung¹⁴^ORCID,Li Ai‐Hsien Adams⁵,Chien Ting‐Ying⁶^ORCID,Nguyen Van‐Chuc²³^ORCID

Affiliation:

1. Department of Information Management Yuan Ze University Taoyuan Taiwan

2. University of Economics, The University of Danang Danang Vietnam

3. Teaching and Research Team for Business Intelligence University of Economics, The University of Danang Danang Vietnam

4. Innovation Center for Big Data and Digital Convergence Yuan Ze University Taoyuan Taiwan

5. Division of Cardiology Far Eastern Memorial Hospital Taipei Taiwan

6. Department of Computer Science and Engineering Yuan Ze University Taoyuan Taiwan

Funder

Ministry of Science and Technology, Taiwan

Publisher

Wiley

Subject

Cancer Research,Oncology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/ijc.33245

Reference50 articles.

1. Molecular epidemiology of hepatitis B, C, D and E viruses among children in Moscow, Russia

2. HEPATITIS VIRUSES A, B, C, D, E AND G: IMPLICATIONS FOR DENTAL PERSONNEL

3. WHO.What is hepatitis?https://www.who.int/features/qa/76/en/. Accessed February 29 2020.

4. WHO World Hepatitis Day2019Invest in eliminating hepatitis.https://www.who.int/news‐room/campaigns/world‐hepatitis‐day/2019. Accessed February 28 2020.

5. Towards the eradication of hepatitis B in Taiwan

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