Artificial intelligence-based model for diagnosing Helicobacter pylori in whole-slide images
Our research presents an AI - based predictive model for <i>H. pylori</i> infection, which significantly enhances clinical efficiency and diagnostic accuracy. Currently, we are conducting multi-center validation to enhance the model's generalization capability.
Authors
- Kunyang Teng (ORCID: https://orcid.org/0000-0003-2396-5414)
- Yilin Duan (ORCID: https://orcid.org/0009-0001-1940-9581)
- Xiaoyu Yan (ORCID: https://orcid.org/0009-0008-3356-6939)
- Lihua Ren
- Lihua Zhang (ORCID: https://orcid.org/0000-0003-0467-4347)
- Hansheng Li (ORCID: https://orcid.org/0000-0002-0923-196X)
- Lei Cui (ORCID: https://orcid.org/0000-0002-8478-3297)
- Zhe Chen (ORCID: https://orcid.org/0009-0005-2285-2890)
Institutions
- Northwest University (CN)
- Zhongda Hospital Southeast University (CN)
Publication Details
- Journal
- Frontiers in Medicine
- Published
- 2025-06-11
- DOI
- https://doi.org/10.3389/fmed.2025.1594614
- Citations
- 1
- Primary Topic
- Colorectal Cancer Screening and Detection
- Type
- article
- Field-Weighted Citation Impact
- 1.05
Funders
- China Postdoctoral Science Foundation
- Government of Jiangsu Province
- Southeast University