Application of a deep learning algorithm for the diagnosis of HCC
The clinical applicability of deep learning in HCC diagnosis is potentially huge, especially considering the expected increase in the incidence and mortality of HCC worldwide. Early diagnosis through deep learning can lead to earlier definitive management, particularly for at-risk patients. The model can be broadly deployed for patients undergoing a triphasic contrast CT scan of the liver to reduce the currently high mortality rate of HCC.
Authors
- Jian‐Liang Lu (ORCID: https://orcid.org/0000-0002-1099-0875)
- Cheng-Zhi Peng (ORCID: https://orcid.org/0000-0002-4753-5243)
- K.W. Chiu (ORCID: https://orcid.org/0000-0002-7930-1193)
- Philip L. H. Yu (ORCID: https://orcid.org/0000-0002-9449-0420)
- Xinping Shen
- Zijie Deng
- Gilbert C.S. Lui (ORCID: https://orcid.org/0009-0005-7078-7966)
- Wai Keung Li
- Jian Zhou (ORCID: https://orcid.org/0000-0002-8654-6439)
- Lung‐Yi Mak (ORCID: https://orcid.org/0000-0002-2266-3935)
- Peng Xiao (ORCID: https://orcid.org/0000-0003-0075-581X)
- Hao Feng Chan
- Man‐Fung Yuen (ORCID: https://orcid.org/0000-0001-7985-7725)
- Jiaqi Guo (ORCID: https://orcid.org/0000-0002-0254-0401)
- Ho Ming Cheng (ORCID: https://orcid.org/0000-0001-8404-223X)
- Xianhua Mao (ORCID: https://orcid.org/0000-0003-4050-4759)
- Juan Wu (ORCID: https://orcid.org/0000-0001-6444-2535)
- Jin‐Hua Huang (ORCID: https://orcid.org/0000-0001-5794-2240)
- Ni Li (ORCID: https://orcid.org/0009-0004-1364-5585)
- King Ming Kwok
- Sarah M. Yu
- Wai‐Kay Seto (ORCID: https://orcid.org/0000-0002-9012-313X)
- P Lam
- Y C Ho
- Wai Kuen Kan
- Cynthia Hui
- Vivien W M Tsui
Institutions
- Sun Yat-sen University (CN)
- Chinese University of Hong Kong (HK)
- Kwong Wah Hospital (CN)
- Queen Mary Hospital (CN)
- Pamela Youde Nethersole Eastern Hospital (CN)
- Education University of Hong Kong (HK)
- University of Hong Kong - Shenzhen Hospital (CN)
- Sun Yat-sen University Cancer Center (CN)
- Queen Elizabeth Hospital (CN)
- State Key Laboratory of Oncology in South China
- University of Hong Kong (HK)
Publication Details
- Journal
- JHEP Reports
- Published
- 2024-09-16
- DOI
- https://doi.org/10.1016/j.jhepr.2024.101219
- Citations
- 14
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 5.66
Funders
- Queen Mary University of London
- Sun Yat-sen University
- University of Hong Kong
- Education University of Hong Kong
- Innovation and Technology Fund
- State Key Laboratory of Oncology in South China
- Health and Medical Research Fund
- Sun Yat-sen University Cancer Center