
Research Article
Diagnosis Hepatitis B Using Machine and Deep Learning: Survey
@INPROCEEDINGS{10.1007/978-3-031-33614-0_8, author={Gehad Ahmed Soltan Abd-Elaleem and Fahad Elsheref and Rabab Maher and Ahmed Elsayed and Doaa S. Elzanfaly and Ahmed Sharaf Eldin}, title={Diagnosis Hepatitis B Using Machine and Deep Learning: Survey}, proceedings={Big Data Technologies and Applications. 11th and 12th EAI International Conference, BDTA 2021 and BDTA 2022, Virtual Event, December 2021 and 2022, Proceedings}, proceedings_a={BDTA}, year={2023}, month={5}, keywords={Artificial Intelligence Hepatitis B Liver Diseases Machine Learning Deep Learning DL AI HBV HCV HCC ML}, doi={10.1007/978-3-031-33614-0_8} }
- Gehad Ahmed Soltan Abd-Elaleem
Fahad Elsheref
Rabab Maher
Ahmed Elsayed
Doaa S. Elzanfaly
Ahmed Sharaf Eldin
Year: 2023
Diagnosis Hepatitis B Using Machine and Deep Learning: Survey
BDTA
Springer
DOI: 10.1007/978-3-031-33614-0_8
Abstract
Machine Learning (ML) improves healthcare systems by helping to reach a proper diagnosis and reducing the diagnosis faults such as severe illness, cancer, inflammatory diseases, other diseases, and pathology. Many studies found that ML-based systems can be better than humans in more critical tasks. The study of liver disease diagnosis is very important, especially the diagnosis of hepatic virus diseases, which are among the most problems facing the liver, particularly Hepatitis B, as this virus is ranked by the World Health Organization (WHO) as the second most dangerous carcinogen in the world, after tobacco. Therefore, it is crucial to identify this harmful virus as soon as possible. As a result, the field of machine learning has focused on the early detection of Liver Hepatitis, particularly virus B. In this paper, we surveyed machine and deep-learning liver disease diagnosis, particularly hepatitis B, and we demonstrated the findings of previous experimental studies and results, as well as the limitations and future work that is suggested in this area.