Zhou Y, Liu RD, Gong H, Yuan XL, Hu B, Huang ZY. Multimodal artificial intelligence system for detecting a small esophageal high-grade squamous intraepithelial neoplasia: A case report.
World J Gastrointest Endosc 2025;
17:101233. [PMID:
39850915 PMCID:
PMC11752473 DOI:
10.4253/wjge.v17.i1.101233]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/09/2024] [Revised: 11/21/2024] [Accepted: 12/06/2024] [Indexed: 01/16/2025] Open
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.
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