Preoperative model for predicting early recurrence in hepatocellular carcinoma patients using radiomics and deep learning: A multicenter study
The most efficient model integrated the tumor region with the peritumoral 5 mm and 10 mm regions. This model provides a noninvasive, effective, and reliable method for predicting ER after curative ablation of HCC.
Authors
- Weidong Jia (ORCID: https://orcid.org/0000-0002-2664-2031)
- Ming-Tong Wei
- Yao Ling (ORCID: https://orcid.org/0000-0001-5797-3231)
- X Lei
- Lei Tang (ORCID: https://orcid.org/0009-0006-1948-1643)
- Zi-Ling Xu
- Xiang-Yi Bu
- Yu Zhu (ORCID: https://orcid.org/0000-0002-1998-0294)
- Yonghai Li (ORCID: https://orcid.org/0000-0001-8911-0481)
- Jianlin Lu
- Guixiang Qian
Institutions
- University of Science and Technology of China (CN)
- Shandong University (CN)
- Bengbu Medical College (CN)
- Anhui Medical University (CN)
- Wenzhou Medical University (CN)
- Xiyuan Hospital (CN)
- Anhui Provincial Hospital (CN)
- First Affiliated Hospital of Anhui Medical University (CN)
- Second Affiliated Hospital of Anhui Medical University (CN)
- Third People's Hospital of Hefei (CN)
- Zhejiang Taizhou Hospital (CN)
Publication Details
- Journal
- World Journal of Gastrointestinal Oncology
- Published
- 2025-06-13
- DOI
- https://doi.org/10.4251/wjgo.v17.i6.106608
- Citations
- 1
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 1.36