A Transfer Learning Radiomics Nomogram to Predict the Postoperative Recurrence of Advanced Gastric Cancer
TLS-WSI can be used to predict postoperative recurrence in AGC, whereas TLRM is more effective. TL can effectively improve the performance of clinical research models with a small sample size.
Authors
- Liebin Huang (ORCID: https://orcid.org/0000-0001-8180-3697)
- Shi‐Ting Feng (ORCID: https://orcid.org/0000-0002-0869-7290)
- Xiangguang Chen (ORCID: https://orcid.org/0000-0003-4368-4820)
- Zhiqi Yang (ORCID: https://orcid.org/0000-0002-4139-4371)
- Qinxian Chen
- Wansheng Long (ORCID: https://orcid.org/0000-0002-1331-1858)
- Xiaofeng Chen (ORCID: https://orcid.org/0000-0002-0457-6854)
- Bao Feng (ORCID: https://orcid.org/0000-0001-6389-8055)
- Huimin Xue (ORCID: https://orcid.org/0009-0008-4207-9972)
- Tao Zhou (ORCID: https://orcid.org/0000-0001-5486-4355)
- Jiangfeng Shi
- Yü Liu (ORCID: https://orcid.org/0000-0003-4404-7006)
- Cuixia Wan
Institutions
- Sun Yat-sen University (CN)
- Guilin University of Aerospace Technology (CN)
- Meizhou City People's Hospital (CN)
- The First Affiliated Hospital, Sun Yat-sen University (CN)
- Jiangmen Central Hospital (CN)
- First Affiliated Hospital of Jinan University (CN)
Publication Details
- Journal
- Journal of Gastroenterology and Hepatology
- Published
- 2024-12-27
- DOI
- https://doi.org/10.1111/jgh.16863
- Citations
- 1
- Primary Topic
- Gastric Cancer Management and Outcomes
- Type
- article
- Field-Weighted Citation Impact
- 0.42