Impact of real-time artificial intelligence integration on detection of gastric lesions: an exploratory single-center before-and-after study using low-definition routine endoscopy

Clinical Endoscopy 2026 Open access

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Authors: Hwijun Lee, Huynh Cong Bang, Seokho Cho, Jungmin Ha, Tran Thien Khiem, Le Viet Tung, La Vinh Phuc, Duong Trong Si, Trần Thế Đủ, Diem Thi‐Ngoc Vo, Vo Nguyen Trung
DOI: 10.5946/ce.2025.272
Cited by: 1
References: 33

Abstract

BACKGROUND: Early detection of gastric neoplasia, particularly subcentimeter lesions, using upper gastrointestinal (GI) endoscopy remains challenging. This study evaluated the impact of a real-time artificial intelligence (AI) detection system on the lesion detection rate (LDR) during routine upper GI endoscopy performed using a low-definition platform commonly used in resource-limited settings, with a focus on lesions ≤0.5 cm. METHODS: Diagnostic upper GI endoscopies performed between September 2024 and May 2025 were analyzed. LDRs were compared between the pre- and post-AI periods, including subgroup analyses by lesion size and type. RESULTS: A total of 2,329 patients were included (1,491 pre-AI, 838 post-AI). After AI implementation, overall LDR per person increased from 1.15±0.45 to 1.20±0.57 (p

Fields of Study & Subjects

Colorectal Cancer Screening and Detection Gastrointestinal Bleeding Diagnosis and Treatment Gastric Cancer Management and Outcomes

Publication details

Journal / source
Clinical Endoscopy
Publisher
The Korean Society of Gastrointestinal Endoscopy
Volume
59
Issue
3
Pages
408–416
Publication date
22 April 2026
Language
EN