• Search
  • Advanced Search
Clin Mol Hepatol > Accepted Articles
Correspondence
Reply to Unlocking the future: machine learning sheds light on prognostication for early-stage hepatocellular carcinoma
Chun-Ting Ho1, Elise Chia-Hui Tan2, Chien-Wei Su3,4,5
1Division of Gastroenterology and Hepatology, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan
2Department of Health Service Administration, College of Public Health, China Medical University, Taichung, Taiwan
3Division of General Medicine, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan
4School of Medicine, College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
5Institute of Clinical Medicine, School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
Correspondence :  Chien-Wei Su ,
Tel: +886-2-28712121 ext. 3352, Fax: +886-2-28739318, Email: cwsu2@vghtpe.gov.tw
Received: May 16, 2024   Accepted: May 19, 2024
TOOLS
METRICS Graph View
  • 0 Crossref
  •  0 Scopus
  • 292 View
  • 7 Download
Related articles

Unlocking the future: machine learning sheds light on prognostication for early-stage hepatocellular carcinoma

Conventional and machine learning-based risk scores for patients with early-stage hepatocellular carcinoma

Recent advances in the management of hepatocellular carcinoma2024 January;30(1)

Assessing the performance of ChatGPT in answering questions regarding cirrhosis and hepatocellular carcinoma2023 July;29(3)

Factors associated with unrecognized cirrhosis in patients with hepatocellular carcinoma2023 April;29(2)

Editorial Office
The Korean Association for the Study of the Liver
Room A1210, 53 Mapo-daero(MapoTrapalace, Dowha-dong), Mapo-gu, Seoul, 04158, Korea
TEL: +82-2-703-0051   FAX: +82-2-703-0071    E-mail: kasl@kams.or.kr
Copyright © The Korean Association for the Study of the Liver.         
COUNTER
TODAY : 1560
TOTAL : 1892397
Close layer