Digital pathology-based prognostic model for hepatocellular carcinoma: Integrating pathomics signatures with clinical parameters for recurrence prediction and biological interpretation
This study establishes a robust digital pathology framework that not only improves HCC recurrence prediction beyond conventional biomarkers but also provides mechanistic insights into tumor-immune crosstalk.
Authors
- Peng Hu (ORCID: https://orcid.org/0000-0001-7864-3514)
- Yu Zhang (ORCID: https://orcid.org/0000-0003-3474-422X)
- Yu Zhu (ORCID: https://orcid.org/0000-0002-5430-7847)
- Shao-wei Li (ORCID: https://orcid.org/0000-0002-3276-1037)
- Qi Wang (ORCID: https://orcid.org/0000-0003-2414-1652)
- Zhenyu Jiang (ORCID: https://orcid.org/0000-0002-7252-1898)
- Yongping Huang
- Yongfu Xu (ORCID: https://orcid.org/0000-0003-3152-8505)
- Long Liu
Institutions
- Anhui Medical University (CN)
- Wenzhou Medical University (CN)
- Inner Mongolia University of Science and Technology (CN)
- First Affiliated Hospital of Anhui Medical University (CN)
- Second Affiliated Hospital of Zhejiang University (CN)
- Zhejiang Taizhou Hospital (CN)
- Baotou Medical College (CN)
Publication Details
- Journal
- Computer Methods and Programs in Biomedicine
- Published
- 2025-11-27
- DOI
- https://doi.org/10.1016/j.cmpb.2025.109180
- Primary Topic
- Hepatocellular Carcinoma Treatment and Prognosis
- Type
- article
- Field-Weighted Citation Impact
- 0.00