AIMC Topic: Barrett Esophagus
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Endoscopic Surveillance of Barrett's Esophagus Using Volumetric Laser Endomicroscopy With Artificial Intelligence Image Enhancement.
Gastroenterology
May 9, 2019
A survey on Barrett's esophagus analysis using machine learning.
Computers in biology and medicine
Mar 30, 2018
This work presents a systematic review concerning recent studies and technologies of machine learning for Barrett's esophagus (BE) diagnosis and treatment. The use of artificial intelligence is a brand new and promising way to evaluate such disease. ...
Application of deep learning models in the pathological classification and staging of esophageal cancer: A focus on Wave-Vision Transformer.
World journal of gastroenterology
May 21, 2025
BACKGROUND: Esophageal cancer is the sixth most common cancer worldwide, with a high mortality rate. Early prognosis of esophageal abnormalities can improve patient survival rates. The progression of esophageal cancer follows a sequence from esophagi...
The role of artificial intelligence-assisted endoscopy surveillance in clinical practice: controversies and future perspectives.
Gastrointestinal endoscopy
Aug 1, 2024
A deep learning system for detection of early Barrett's neoplasia: a model development and validation study.
The Lancet. Digital health
Dec 1, 2023
BACKGROUND: Computer-aided detection (CADe) systems could assist endoscopists in detecting early neoplasia in Barrett's oesophagus, which could be difficult to detect in endoscopic images. The aim of this study was to develop, test, and benchmark a C...
Artificial intelligence in upper GI endoscopy - current status, challenges and future promise.
Journal of gastroenterology and hepatology
Jan 1, 2021
White-light endoscopy with biopsy is the current gold standard modality for detecting and diagnosing upper gastrointestinal (GI) pathology. However, missed lesions remain a challenge. To overcome interobserver variability and learning curve issues, a...
CAESNet: Convolutional AutoEncoder based Semi-supervised Network for improving multiclass classification of endomicroscopic images.
Journal of the American Medical Informatics Association : JAMIA
Nov 1, 2019
OBJECTIVE: This article presents a novel method of semisupervised learning using convolutional autoencoders for optical endomicroscopic images. Optical endomicroscopy (OE) is a newly emerged biomedical imaging modality that can support real-time clin...
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