Artificial intelligence-assisted real-time nasopharyngeal cancer diagnostic model enhances rhinologist performance: a prospective multi-reader study
AI-assisted nasoendoscopic evaluation significantly enhances diagnostic accuracy, efficiency and interobserver consistency, particularly among less-experienced clinicians. These findings support the clinical integration of real-time AI tools to augment NPC recognition and standardize diagnostic performance across varying expertise levels.
Authors
- Z. Huang (ORCID: https://orcid.org/0000-0002-7195-3189)
- Wendong Liu (ORCID: https://orcid.org/0000-0001-7562-3702)
- Lu Yin (ORCID: https://orcid.org/0000-0002-5075-5263)
- Pengyu Jie
- Rui He
- Wanquan Liu
- Yihui Wen
- Weiping Wen (ORCID: https://orcid.org/0000-0002-1075-7475)
- Zhangfeng Wang
- Wenbin Lei
- Yongquan Wang
- Huanhuan Lv
Institutions
- National Sun Yat-sen University (TW)
- Sun Yat-sen University (CN)
- The Seventh Affiliated Hospital of Sun Yat-sen University (CN)
- Sun Yat-sen Memorial Hospital (CN)
- The First Affiliated Hospital, Sun Yat-sen University (CN)
Publication Details
- Journal
- Annals of Medicine
- Published
- 2026-02-02
- DOI
- https://doi.org/10.1080/07853890.2026.2620335
- Primary Topic
- Sinusitis and nasal conditions
- Type
- article
- Field-Weighted Citation Impact
- 0.00