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Structured Approach to Colonoscopy Technique Optimization: A Single-Center Experience with Novice Endoscopists

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Artificial intelligence in gastrointestinal endoscopy.

Rahul Pannala¹, Kumar Krishnan², Joshua Melson³

¹Department of Gastroenterology and Hepatology, Mayo Clinic, Scottsdale, Arizona.

Videogie : an Official Video Journal of the American Society for Gastrointestinal Endoscopy

|December 15, 2020

Summary

This summary is machine-generated.

Artificial intelligence (AI) is revolutionizing gastroenterology (GE) by enhancing endoscopic image analysis. AI applications improve the accuracy and efficiency of diagnosing conditions like colorectal polyps and gastric cancer.

Keywords:

ADR, adenoma detection rate AI, artificial intelligence AMR, adenoma miss rate ANN, artificial neural network BE, Barrett’s esophagus CAD, computer-aided diagnosis CADe, CAD studies for colon polyp detection CADx, CAD studies for colon polyp classification CI, confidence interval CNN, convolutional neural network CRC, colorectal cancer DL, deep learning GI, gastroenterology HD-WLE, high-definition white light endoscopy HDWL, high-definition white light ML, machine learning NBI, narrow-band imaging NPV, negative predictive value PIVI, preservation and Incorporation of Valuable Endoscopic Innovations SVM, support vector machine VLE, volumetric laser endomicroscopy WCE, wireless capsule endoscopy WL, white light

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2026-06-19T13:38:49.737499+00:00