Current Status and Future Directions of Research on Artificial Intelligence in Nasopharyngolaryngoscopy

The nasopharyngolaryngoscopy (NPL) has emerged as a valuable tool for detecting early cases of head and neck cancers (HNCs). However, misdiagnoses and missed diagnoses are still common phenomena. The expertise of examining physicians often serves as the primary limiting factor, leading to issues such as incomplete visualization, imprecise identification, and unclear vision. Over recent years, the application of artificial intelligence (AI) in medical imaging, particularly in the realm of gastrointestinal endoscopy, has instigated revolutionary changes in site quality control, lesion identification, and report generation. However, there remains a lack of standardized guidelines for the proper application of NPL across various countries. While AI-related research in NPL is still in its nascent stages, it shows substantial potential for clinical application and endoscopic training. In this paper, we set our sights on reviewing the current clinical applications and summarizing the primary shortcomings of NPL. In addition, we encapsulate the progress of AI application within gastrointestinal endoscopy and NPL. Drawing from real-world clinical practice, we propose future directions and prospects for AI research in NPL. We firmly believe that the pace of clinical application of AI in NPL will accelerate significantly in the near future.