- Artificial intelligence (AI)-based applications have transformed several industries and are widely used in various consumer products and services. In medicine, AI is primarily being used for image classification and natural language processing and has great potential to affect image-based specialties such as radiology, pathology, and gastroenterology (GE). This document reviews the reported applications of AI in GE, focusing on endoscopic image analysis.
- The endoscopic evaluation of narrow-band imaging (NBI) zoom imagery in Barrett’s esophagus (BE) is associated with suboptimal diagnostic accuracy and poor interobserver agreement. Computer-aided diagnosis (CAD) systems may assist endoscopists in the characterization of Barrett’s mucosa. Our aim was to demonstrate the feasibility of a deep-learning CAD system for tissue characterization of NBI zoom imagery in BE.
- GI endoscopy has evolved from a simple diagnostic tool to an entire field incorporating highly complex technical and cognitive skills to perform an ever-increasing number of tasks. Key to high-quality endoscopy is the acquisition of images that contain useful information. For any given procedure, the endoscopic video stream contains thousands of single-frame images, most of which lack clinically relevant information. Thus, the endoscopist must possess the technical skill to obtain meaningful images and to sort through these images (at an subconscious level) to extract relevant information by recognizing and interpreting features and patterns so as to ultimately use this information to make an appropriate clinical decision.
- The visual detection of early esophageal neoplasia (high-grade dysplasia and T1 cancer) in Barrett’s esophagus (BE) with white-light and virtual chromoendoscopy still remains challenging. The aim of this study was to assess whether a convolutional neural artificial intelligence network can aid in the recognition of early esophageal neoplasia in BE.
- Endoscopy is one of the cornerstones in the field of gastroenterology. The original fiberoptic endoscope was developed in the 1950s. From this point in time and decade after decade the field of endoscopy continues to this day to grow and evolve. Endoscopic retrograde cholangiography was developed in the 1970s and EUS in the 1980s, further showing the potential of endoscopy to have no boundaries. The image quality of the scope is now high-definition white light along with optical enhancements such as narrow-band imaging (NBI), with the goal to improve mucosal surface area inspection to both identify and interpret abnormal areas.