Exploring artificial intelligence-assisted diagnosis of esophageal squamous cell carcinoma: insights from a clinical trial

Esophageal squamous cell carcinoma (ESCC) remains a significant global health burden, with persistently high incidence and mortality rates [1]. Early detection and timely treatment are essential for improving patients outcomes, with esophagogastroduodenoscopy playing an irreplaceable role in this process [2]. The endoscopic features of superficial ESCC are however often subtle compared with the surrounding mucosa, necessitating the integration of multiple modalities, such as white-light imaging (WLI), narrow-band imaging (NBI), and iodine staining, for effective screening. The detection rate of superficial ESCC varies considerably, influenced by disparities in endoscopic equipment, as well as the skills and experience of individual endoscopists.