Predicting early recurrence in locally advanced gastric cancer after gastrectomy using CT-based deep learning model: a multicenter study
The DLER MLP based on CT images was able to predict early recurrence of patients with LAGC and served as a useful tool for optimizing treatment strategies and monitoring.
Authors
- Lingling Zhou (ORCID: https://orcid.org/0000-0002-2274-6749)
- Minjiang Chen (ORCID: https://orcid.org/0000-0002-4040-6115)
- Xinyu Guo (ORCID: https://orcid.org/0000-0002-7282-7379)
- Jiansong Ji (ORCID: https://orcid.org/0000-0002-6026-3676)
- Shuiwei Xia
- Mingzhen Chen (ORCID: https://orcid.org/0000-0003-2340-1221)
- Chenying Lu
- Shuang Liu (ORCID: https://orcid.org/0000-0003-4046-5905)
- Feng Chen
- Yongjun Chen (ORCID: https://orcid.org/0000-0002-6486-2000)
- Qiang Li (ORCID: https://orcid.org/0000-0002-8686-0890)
- Lingyi Zhu
- Liyun Zheng (ORCID: https://orcid.org/0000-0001-7750-4109)
Institutions
- Ningbo University (CN)
- Wenzhou Medical University (CN)
- Lishui University (CN)
- First Affiliated Hospital Zhejiang University (CN)
- Zhejiang University (CN)
Publication Details
- Journal
- International Journal of Surgery
- Published
- 2024-12-23
- DOI
- https://doi.org/10.1097/js9.0000000000002184
- Citations
- 7
- Primary Topic
- Gastric Cancer Management and Outcomes
- Type
- article
- Field-Weighted Citation Impact
- 2.93