AI support for colonoscopy quality control using CNN and transformer architectures
The AI-assisted quality system, based on the EfficientNetB2 model, integrates four key quality control indicators for colonoscopy. This integration enables medical institutions to comprehensively manage and enhance these indicators using a single model, showcasing promising potential for clinical applications.
Authors
- Kaijian Xia (ORCID: https://orcid.org/0009-0004-4688-9009)
- Yu‐Qiang Ding (ORCID: https://orcid.org/0000-0003-1202-4635)
- Ganhong Wang
- Xiaodan Xu (ORCID: https://orcid.org/0000-0001-8338-1600)
- Zihao Zhang (ORCID: https://orcid.org/0000-0001-9286-8189)
- Jian Chen (ORCID: https://orcid.org/0000-0003-0054-991X)
- Jingjie Zhou
Institutions
- Soochow University (CN)
- Suzhou Traditional Chinese Medicine Hospital (CN)
Publication Details
- Journal
- BMC Gastroenterology
- Published
- 2024-08-09
- DOI
- https://doi.org/10.1186/s12876-024-03354-0
- Citations
- 14
- Primary Topic
- AI in cancer detection
- Type
- article
- Field-Weighted Citation Impact
- 4.86