Multimodal artificial intelligence system for detecting a small esophageal high-grade squamous intraepithelial neoplasia: A case report.

Abstract

Background: Recent advancements in artificial intelligence (AI) have significantly enhanced the capabilities of endoscopic-assisted diagnosis for gastrointestinal diseases. AI has shown great promise in clinical practice, particularly for diagnostic support, offering real-time insights into complex conditions such as esophageal squamous cell carcinoma.

Case summary: In this study, we introduce a multimodal AI system that successfully identified and delineated a small and flat carcinoma during esophagogastroduodenoscopy, highlighting its potential for early detection of malignancies. The lesion was confirmed as high-grade squamous intraepithelial neoplasia, with pathology results supporting the AI system's accuracy. The multimodal AI system offers an integrated solution that provides real-time, accurate diagnostic information directly within the endoscopic device interface, allowing for single-monitor use without disrupting endoscopist's workflow.

Conclusion: This work underscores the transformative potential of AI to enhance endoscopic diagnosis by enabling earlier, more accurate interventions.