Assessment of the efficiency and accuracy of an artificial intelligence assistive system in the diagnosis of Pap cervical atypical glandular cell cytology
To the authors' knowledge, this is the first study focusing on assessment of AGCs on an artificial intelligence system. The findings demonstrated that the AICyte system offers substantial improvements in efficiency and diagnostic consistency for the interpretation of AGCs and significantly reduces slide reading time. These results support the potential of AI to augment performance, especially in resource-limited settings or high-volume screening environments.
Authors
- Terrell E. Jones (ORCID: https://orcid.org/0000-0002-1109-5231)
- Changzhong Li (ORCID: https://orcid.org/0000-0001-5654-1031)
- Chengquan Zhao (ORCID: https://orcid.org/0000-0001-7524-3048)
- Xiangchen Wu (ORCID: https://orcid.org/0000-0001-6601-5879)
- Xin Zhang (ORCID: https://orcid.org/0000-0002-3833-2938)
- Xiaoqian Wang (ORCID: https://orcid.org/0000-0002-1283-7786)
- Yixuan Liu (ORCID: https://orcid.org/0000-0003-3932-1592)
- Yingbin Li (ORCID: https://orcid.org/0000-0002-0789-9739)
- Xianxu Zeng (ORCID: https://orcid.org/0000-0002-0457-9908)
- Xinru Bai (ORCID: https://orcid.org/0000-0002-6863-278X)
- David Starr
- Xing Dong
Institutions
- CE Technologies (United Kingdom) (GB)
- University of Pittsburgh Medical Center (US)
- Third Affiliated Hospital of Zhengzhou University (CN)
Publication Details
- Journal
- Cancer Cytopathology
- Published
- 2025-10-09
- DOI
- https://doi.org/10.1002/cncy.70056
- Primary Topic
- Cervical Cancer and HPV Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00