Assessment of microorganism detection in ThinPrep Papanicolaou tests utilizing the Hologic Genius Digital Diagnostics System
Very high sensitivity was observed for TPPTs across 3 of 4 common microorganisms on the HGDDS, although sensitivity was relatively lower for detecting HSV. Understanding morphologic patterns of various microorganisms in detection misses by the HGDDS may help guide the implementation of AI-assisted cervical cancer screening systems.
Authors
- Jonee Matsko (ORCID: https://orcid.org/0009-0003-1011-3949)
- Amy Colaizzi
- Yuhong Ye
- Chengquan Zhao
- Liron Pantanowitz
- Ali Seemaab
Institutions
- Fujian Medical University (CN)
- University of Pittsburgh (US)
- Computational Diagnostics (United States) (US)
- First Affiliated Hospital of Fujian Medical University (CN)
- University of Pittsburgh Medical Center (US)
Publication Details
- Journal
- American Journal of Clinical Pathology
- Published
- 2025-10-23
- DOI
- https://doi.org/10.1093/ajcp/aqaf126
- Primary Topic
- AI in cancer detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00