AIMC Topic: Gastritis
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Deep learning in gastric tissue diseases: a systematic review.
BMJ open gastroenterology
Mar 26, 2020
BACKGROUND: In recent years, deep learning has gained remarkable attention in medical image analysis due to its capacity to provide results comparable to specialists and, in some cases, surpass them. Despite the emergence of deep learning research on...
Convolutional Neural Network for Differentiating Gastric Cancer from Gastritis Using Magnified Endoscopy with Narrow Band Imaging.
Digestive diseases and sciences
Oct 4, 2019
BACKGROUND: Early detection of early gastric cancer (EGC) allows for less invasive cancer treatment. However, differentiating EGC from gastritis remains challenging. Although magnifying endoscopy with narrow band imaging (ME-NBI) is useful for differ...
A Deep Learning Convolutional Neural Network Can Recognize Common Patterns of Injury in Gastric Pathology.
Archives of pathology & laboratory medicine
Jun 27, 2019
CONTEXT.—: Most deep learning (DL) studies have focused on neoplastic pathology, with the realm of inflammatory pathology remaining largely untouched.
Application of convolutional neural networks for evaluating Helicobacter pylori infection status on the basis of endoscopic images.
Scandinavian journal of gastroenterology
Mar 17, 2019
BACKGROUND AND AIM: We recently reported the role of artificial intelligence in the diagnosis of Helicobacter pylori (H. pylori) gastritis on the basis of endoscopic images. However, that study included only H. pylori-positive and -negative patients,...
Detection of gastritis by a deep convolutional neural network from double-contrast upper gastrointestinal barium X-ray radiography.
Journal of gastroenterology
Oct 3, 2018
BACKGROUND: Deep learning has become a new trend of image recognition tasks in the field of medicine. We developed an automated gastritis detection system using double-contrast upper gastrointestinal barium X-ray radiography.
A Deep Learning Convolutional Neural Network Can Differentiate Between Helicobacter Pylori Gastritis and Autoimmune Gastritis With Results Comparable to Gastrointestinal Pathologists.
Archives of pathology & laboratory medicine
Jan 1, 2022
CONTEXT.—: Pathology studies using convolutional neural networks (CNNs) have focused on neoplasms, while studies in inflammatory pathology are rare. We previously demonstrated a CNN that differentiates reactive gastropathy, Helicobacter pylori gastri...
[A novel attention fusion network-based multiple instance learning framework to automate diagnosis of chronic gastritis with multiple indicators].
Zhonghua bing li xue za zhi = Chinese journal of pathology
Oct 8, 2021
To explore the performance of the attention-multiple instance learning (MIL) framework, an attention fusion network-based MIL, in the automated diagnosis of chronic gastritis with multiple indicators. A total of 1 015 biopsy cases of gastritis diag...
Histopathological Diagnosis System for Gastritis Using Deep Learning Algorithm.
Chinese medical sciences journal = Chung-kuo i hsueh k'o hsueh tsa chih
Sep 30, 2021
Objective To develope a deep learning algorithm for pathological classification of chronic gastritis and assess its performance using whole-slide images (WSIs). Methods We retrospectively collected 1,250 gastric biopsy specimens (1,128 gastritis, 122...
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...
[A Case of Eosinophilic Enteritis Needed to Distinguish from a Tumor of the Small Intestine].
Gan to kagaku ryoho. Cancer & chemotherapy
Nov 1, 2016
A 75-year-old woman was diagnosed with aplastic anemia 6 months ago and was under follow-up at our hospital. She had originallypresented to our hospital because of ongoing diarrhea and abdominal pain. Her blood tests showed a rise in inflammatorymark...
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