AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Endoscopy, Gastrointestinal

Showing 71 to 80 of 155 articles

Clear Filters

Single Shot Multibox Detector Automatic Polyp Detection Network Based on Gastrointestinal Endoscopic Images.

Computational and mathematical methods in medicine
PURPOSE: In order to resolve the situation of high missed diagnosis rate and high misdiagnosis rate of the pathological analysis of the gastrointestinal endoscopic images by experts, we propose an automatic polyp detection algorithm based on Single S...

A novel Joint-Net model for recognizing small-bowel polyp images.

Minimally invasive therapy & allied technologies : MITAT : official journal of the Society for Minimally Invasive Therapy
INTRODUCTION: To automatically recognize polyps of enteroscopy images and avoid pathological change, a novel Joint-Net has been proposed.

Deep Learning for nasopharyngeal Carcinoma Identification Using Both White Light and Narrow-Band Imaging Endoscopy.

The Laryngoscope
OBJECTIVES/HYPOTHESIS: To develop a deep-learning-based automatic diagnosis system for identifying nasopharyngeal carcinoma (NPC) from noncancer (inflammation and hyperplasia), using both white light imaging (WLI) and narrow-band imaging (NBI) nasoph...

Deep learning-based endoscopic anatomy classification: an accelerated approach for data preparation and model validation.

Surgical endoscopy
BACKGROUND: Photodocumentation during endoscopy procedures is one of the indicators for endoscopy performance quality; however, this indicator is difficult to measure and audit in the endoscopy unit. Emerging artificial intelligence technology may so...

Simultaneous Recognition of Atrophic Gastritis and Intestinal Metaplasia on White Light Endoscopic Images Based on Convolutional Neural Networks: A Multicenter Study.

Clinical and translational gastroenterology
INTRODUCTION: Patients with atrophic gastritis (AG) or gastric intestinal metaplasia (GIM) have elevated risk of gastric adenocarcinoma. Endoscopic screening and surveillance have been implemented in high incidence countries. The study aimed to evalu...

Deep learning system compared with expert endoscopists in predicting early gastric cancer and its invasion depth and differentiation status (with videos).

Gastrointestinal endoscopy
BACKGROUND AND AIMS: We aimed to develop and validate a deep learning-based system that covers various aspects of early gastric cancer (EGC) diagnosis, including detecting gastric neoplasm, identifying EGC, and predicting EGC invasion depth and diffe...

Artificial intelligence-based endoscopic diagnosis of colorectal polyps using residual networks.

PloS one
Convolutional neural networks (CNNs) are widely used for artificial intelligence (AI)-based image classification. Residual network (ResNet) is a new technology that facilitates the accuracy of image classification by CNN-based AI. In this study, we d...

Analytical Modeling of the Interaction Between Soft Balloon-Like Actuators and Soft Tubular Environment for Gastrointestinal Inspection.

Soft robotics
Accessing tubular environment is critical in medicine. For example, gastrointestinal tract related cancers are the leading causes of cancer deaths globally. To diagnose and treat these cancers, clinicians need accessing the gastrointestinal tract, fo...

Using machine-learning algorithms to identify patients at high risk of upper gastrointestinal lesions for endoscopy.

Journal of gastroenterology and hepatology
BACKGROUND AND AIM: Endoscopic screening for early detection of upper gastrointestinal (UGI) lesions is important. However, population-based endoscopic screening is difficult to implement in populous countries. By identifying high-risk individuals fr...