ArticleiScience2023
Deep learning for real-time detection of nasopharyngeal carcinoma during nasopharyngeal endoscopy.
Article in iScience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A Systematic Review of the Clinical Impact of Implementing Artificial Intelligence in Upper Aerodigestive Tract Endoscopy.Head & neck · 2025Pooled it
- A Telemedicine App for Nonrigid Facial Rehabilitation Training Enhanced by Efficient Fully Convolutional Neural Network With Residual Network (EffiFCNN-ResNet) to Improve Accessibility for Patients With Nasopharyngeal Carcinoma Cancer: Randomized Controlled Trial.JMIR mHealth and uHealth · 2026Trial
- Application of artificial intelligence in early warning, diagnosis and precise treatment of head and neck tumors (Review).Molecular and clinical oncology · 2026Review
- Application of YOLO-v7 and YOLO-v8 Transfer Learning Models in Breast Lesion Classification and DiagnosisCurrent medical imaging · 2026Article
- Postoperative outcome analysis of chronic rhinosinusitis using transfer learning with pre-trained foundation models based on endoscopic images: a multicenter, observational study.Biomedical engineering online · 2025Observational
- Real-time artificial intelligence-assisted detection and segmentation of nasopharyngeal carcinoma using multimodal endoscopic data: a multi-center, prospective study.EClinicalMedicine · 2025Article
- Advances in Nasopharyngeal Carcinoma Staging: from the 7th to the 9th Edition of the TNM System and Future Outlook.Current oncology reports · 2025Review
- A deep learning based smartphone application for early detection of nasopharyngeal carcinoma using endoscopic images.NPJ digital medicine · 2024Article
- Advancing precise diagnosis of nasopharyngeal carcinoma through endoscopy-based radiomics analysis.iScience · 2024Article
- Recent Advances in Assessing the Clinical Implications of Epstein-Barr Virus Infection and Their Application to the Diagnosis and Treatment of Nasopharyngeal Carcinoma.Microorganisms · 2023Review
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Authors and funding
9 authors.
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Abstract
Nasopharyngeal carcinoma (NPC) is known for high curability during early stage of the disease, and early diagnosis relies on nasopharyngeal endoscopy and subsequent pathological biopsy. To enhance the early diagnosis rate by aiding physicians in the real-time identification of NPC and directing biopsy site selection during endoscopy, we assembled a dataset comprising 2,429 nasopharyngeal endoscopy video frames from 690 patients across three medical centers. With these data, we developed a deep learning-based NPC detection model using the you only look once (YOLO) network. Our model demonstrated high performance, with precision, recall, mean average precision, and F1-score values of 0.977, 0.943, 0.977, and 0.960, respectively, for internal test set and 0.825, 0.743, 0.814, and 0.780 for external test set at 0.5 intersection over union. Remarkably, our model demonstrated a high inference speed (52.9 FPS), surpassing the average frame rate (25.0 FPS) of endoscopy videos, thus making real-time detection in endoscopy feasible.
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