[Expert consensus on artificial intelligence-assisted data acquisition and clinical application in electronic nasopharyngolaryngoscopy].

In response to the significant clinical challenges associated with current Electronic Nasopharyngolaryngoscopy examinations-including considerable inter-observer variability in physician interpretation, high rates of missed diagnoses for early-stage lesions, and inefficiencies in dynamic functional assessment-this consensus document aims to establish a comprehensive technical framework for Artificial Intelligence（AI） -enabled data acquisition and application. The framework introduces tiered data acquisition standards, comprising a foundational level to ensure clinical accessibility and an advanced level designed for research purposes. It systematically standardizes a dual-mode imaging protocol utilizing both white light and electronic chromoendoscopy. Furthermore, it innovatively proposes a three-tier annotation framework-encompassing regional, characteristic, and diagnostic levels-and establishes rigorous quality control and multi-center validation mechanisms. This document delineates detailed application pathways for AI across five core scenarios: auxiliary detection, auxiliary diagnosis, real-time quality control, automated report generation, and simulation training. Concurrently, it defines ethically compliant data security standards. These technical specifications provide crucial support for enhancing the standardization of nasopharyngeal and laryngeal disease management, facilitate multi-center research collaboration, and hold significant importance for promoting the standardized application of AI within the field of Otorhinolaryngology.