A deep learning model for the diagnosis of gastric neuroendocrine carcinoma
The integration of G-NECNet into routine diagnostic workflows may not only improve the precision of G-NEC classification but also reduce misdiagnosis-related healthcare costs, offering a practical and scalable solution for clinical application.
Authors
- C. Wang
- Wenxu Chen
- Junpeng Lai (ORCID: https://orcid.org/0000-0003-1130-3042)
- Xinke Zhang (ORCID: https://orcid.org/0000-0002-3527-2140)
- Z. Zhao
- Muyan Cai
- Yan Huang
- Lin Zheng
- Zhengyi Zhou
- Tianchen Zhu
- Zhiwei Liao
Institutions
- Fujian Medical University (CN)
- Sun Yat-sen University (CN)
- Sixth Affiliated Hospital of Sun Yat-sen University (CN)
- Sun Yat-sen University Cancer Center (CN)
- Guangzhou Medical University Cancer Hospital (CN)
- Guangzhou Medical University (CN)
Publication Details
- Journal
- Communications Medicine
- Published
- 2026-01-13
- DOI
- https://doi.org/10.1038/s43856-026-01382-3
- Primary Topic
- AI in cancer detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China