Machine Learning–Based Selection of Resection vs Transplant and Survival in Hepatocellular Carcinoma
Findings from this cohort study of patients with HCC indicated that an ML-based decision-support model estimated accurate risk stratification and identified the potential for improved survival through individualized, model-guided treatment selection. These findings suggest clinical utility in supplementing existing guidelines.
Authors
- Ji Won Han (ORCID: https://orcid.org/0000-0003-1456-1450)
- Pil Soo Sung (ORCID: https://orcid.org/0000-0002-5780-9607)
- Jeong Won Jang (ORCID: https://orcid.org/0000-0003-3255-8474)
- Hyun Uk Kim (ORCID: https://orcid.org/0000-0001-7224-642X)
- Seung Kew Yoon (ORCID: https://orcid.org/0000-0002-4476-4868)
- Ho Joong Choi (ORCID: https://orcid.org/0000-0002-0862-098X)
- Young Kyoung You (ORCID: https://orcid.org/0000-0002-8506-0752)
Institutions
- St. Mary's Hospital (US)
- The Catholic University of Korea Seoul St. Mary's Hospital (KR)
- Catholic University of Korea (KR)
Publication Details
- Journal
- JAMA Network Open
- Published
- 2025-09-17
- DOI
- https://doi.org/10.1001/jamanetworkopen.2025.32353
- Citations
- 1
- Primary Topic
- Hepatocellular Carcinoma Treatment and Prognosis
- Type
- article
- Field-Weighted Citation Impact
- 1.32
Funders
- Korea Health Industry Development Institute