Artificial Intelligence in Gastrointestinal Endoscopy: A Comprehensive Systematic Review

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Abstract

Artificial intelligence (AI) has emerged as a transformative force in gastrointestinal (GI) endoscopy, offering enhancements in diagnostic accuracy, lesion detection, and procedural efficiency. This systematic review consolidates current evidence from original research articles on AI applications across various endoscopic procedures, including colonoscopy, esophagogastroduodenoscopy (EGD), and capsule endoscopy. The review highlights AI’s performance in detecting colorectal polyps, gastric cancer, small bowel lesions, and inflammatory bowel disease (IBD). While AI demonstrates high sensitivity and specificity across multiple studies, challenges such as data heterogeneity, integration into clinical workflows, and the need for external validation persist. Future research should focus on large-scale, multicenter trials to validate AI’s efficacy in diverse clinical settings.

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