AIMC Topic: Barrett Esophagus
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Advanced Imaging and Sampling in Barrett's Esophagus: Artificial Intelligence to the Rescue?
Gastrointestinal endoscopy clinics of North America
Oct 26, 2020
Because the current Barrett's esophagus (BE) surveillance protocol suffers from sampling error of random biopsies and a high miss-rate of early neoplastic lesions, many new endoscopic imaging and sampling techniques have been developed. None of these...
Artificial Intelligence and Its Role in Identifying Esophageal Neoplasia.
Digestive diseases and sciences
Oct 15, 2020
Randomized trials have demonstrated that ablation of dysplastic Barrett's esophagus can reduce the risk of progression to cancer. Endoscopic resection for early stage esophageal adenocarcinoma and squamous cell carcinoma can significantly reduce post...
Accuracy of artificial intelligence-assisted detection of upper GI lesions: a systematic review and meta-analysis.
Gastrointestinal endoscopy
Jun 17, 2020
BACKGROUND AND AIMS: Artificial intelligence (AI)-assisted detection is increasingly used in upper endoscopy. We performed a meta-analysis to determine the diagnostic accuracy of AI on detection of gastric and esophageal neoplastic lesions and Helico...
Deep principal dimension encoding for the classification of early neoplasia in Barrett's Esophagus with volumetric laser endomicroscopy.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Jan 24, 2020
Barrett cancer is a treatable disease when detected at an early stage. However, current screening protocols are often not effective at finding the disease early. Volumetric Laser Endomicroscopy (VLE) is a promising new imaging tool for finding dyspla...
Artificial intelligence using convolutional neural networks for real-time detection of early esophageal neoplasia in Barrett's esophagus (with video).
Gastrointestinal endoscopy
Jan 11, 2020
BACKGROUND AND AIMS: 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 wheth...
Deep learning algorithm detection of Barrett's neoplasia with high accuracy during live endoscopic procedures: a pilot study (with video).
Gastrointestinal endoscopy
Jan 10, 2020
BACKGROUND AND AIMS: We assessed the preliminary diagnostic accuracy of a recently developed computer-aided detection (CAD) system for detection of Barrett's neoplasia during live endoscopic procedures.
Finding Barrett's oesophagus: is there a machine learning approach in our future?
The Lancet. Digital health
Dec 23, 2019
Development and validation of a risk prediction model to diagnose Barrett's oesophagus (MARK-BE): a case-control machine learning approach.
The Lancet. Digital health
Dec 5, 2019
BACKGROUND: Screening for Barrett's Oesophagus (BE) relies on endoscopy which is invasive and has a low yield. This study aimed to develop and externally validate a simple symptom and risk-factor questionnaire to screen for patients with BE.
Attention-Based Deep Neural Networks for Detection of Cancerous and Precancerous Esophagus Tissue on Histopathological Slides.
JAMA network open
Nov 1, 2019
IMPORTANCE: Deep learning-based methods, such as the sliding window approach for cropped-image classification and heuristic aggregation for whole-slide inference, for analyzing histological patterns in high-resolution microscopy images have shown pro...
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