Constructing an artificial intelligence-assisted system for the assessment of gastroesophageal valve function based on the hill classification (with video)
By employing deep learning to construct the EfficientNet-Hill AI model, automated Hill classification of GEFV morphology was achieved, aiding endoscopists in improving diagnostic efficiency and accuracy in endoscopic grading, and facilitating the integration of Hill classification into routine endoscopic reports and GERD assessments.
Authors
- Kaijian Xia (ORCID: https://orcid.org/0009-0004-4688-9009)
- Zhenni Wang (ORCID: https://orcid.org/0000-0001-8717-3606)
- Ganhong Wang
- Xiaodan Xu (ORCID: https://orcid.org/0000-0001-8338-1600)
- Luojie Liu (ORCID: https://orcid.org/0000-0003-1806-5155)
- Jian Chen (ORCID: https://orcid.org/0000-0001-9452-6297)
Institutions
- Nanjing University of Chinese Medicine (CN)
- Soochow University (CN)
Publication Details
- Journal
- BMC Medical Informatics and Decision Making
- Published
- 2025-03-24
- DOI
- https://doi.org/10.1186/s12911-025-02973-1
- Citations
- 1
- Primary Topic
- Esophageal and GI Pathology
- Type
- article
- Field-Weighted Citation Impact
- 2.01