Artificial intelligence-assisted endoscopic ultrasound diagnosis of esophageal subepithelial lesions
The EUS-AI model has shown high diagnostic potential for detecting esophageal SELs and identifying their originating layers. EUS-AI has the potential to enhance the diagnostic ability of junior endoscopists in clinical practice.
Authors
- Qing-Yun Cai
- Guoyi Zhou (ORCID: https://orcid.org/0000-0002-5667-7411)
- A.L. Zhang
- Jintao Guo (ORCID: https://orcid.org/0000-0001-5722-6359)
- Wen Liu (ORCID: https://orcid.org/0000-0003-0532-9051)
- Beibei Sun (ORCID: https://orcid.org/0000-0002-6007-8550)
- Zhe Wang (ORCID: https://orcid.org/0000-0002-7006-075X)
- Shupeng Wang (ORCID: https://orcid.org/0000-0002-9283-3397)
- Siyu Sun (ORCID: https://orcid.org/0000-0002-7308-0473)
- D. Jiang (ORCID: https://orcid.org/0000-0002-3035-7807)
- Ying-Huei Wu
Institutions
- Shenzhen Metro (China) (CN)
- ZTE (China) (CN)
- Liaoning Provincial People's Hospital (CN)
- Ministry of Education (KN)
- China Medical University (CN)
Publication Details
- Journal
- Surgical Endoscopy
- Published
- 2025-05-07
- DOI
- https://doi.org/10.1007/s00464-025-11767-5
- Citations
- 1
- Primary Topic
- Esophageal Cancer Research and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 2.01
Funders
- Shengjing Hospital
- Shenyang Young and Middle-aged Science and Technology Innovation Talent Support Program