AI Medical Compendium Journal:
Scandinavian journal of gastroenterology

Showing 1 to 8 of 8 articles

Efficient polyp detection algorithm based on deep learning.

Scandinavian journal of gastroenterology
OBJECTIVE: Colon polyp detection is crucial in reducing the incidence of colorectal cancer. However, due to the diverse morphology of colon polyps, their high similarity to surrounding tissues, and the difficulty of detecting small target polyps, fal...

A clinical pilot trial of an artificial intelligence-driven smart phone application of bowel preparation for colonoscopy: a randomized clinical trial.

Scandinavian journal of gastroenterology
BACKGROUND: High-quality bowel preparation is paramount for a successful colonoscopy. This study aimed to explore the effect of artificial intelligence-driven smartphone software on the quality of bowel preparation.

Deep learning analysis for differential diagnosis and risk classification of gastrointestinal tumors.

Scandinavian journal of gastroenterology
OBJECTIVES: Recently, artificial intelligence (AI) has been applied to clinical diagnosis. Although AI has already been developed for gastrointestinal (GI) tract endoscopy, few studies have applied AI to endoscopic ultrasound (EUS) images. In this st...

Using deep learning models in magnetic resonance cholangiopancreatography images to diagnose common bile duct stones.

Scandinavian journal of gastroenterology
BACKGROUNDS AND AIMS: Magnetic resonance cholangiopancreatography (MRCP) plays a significant role in diagnosing common bile duct stones (CBDS). Currently, there are no studies to detect CBDS by using the deep learning (DL) model in MRCP. This study a...

Using deep learning and explainable artificial intelligence to assess the severity of gastroesophageal reflux disease according to the Los Angeles Classification System.

Scandinavian journal of gastroenterology
OBJECTIVES: Gastroesophageal reflux disease (GERD) is a complex disease with a high worldwide prevalence. The Los Angeles classification (LA-grade) system is meaningful for assessing the endoscopic severity of GERD. Deep learning (DL) methods have be...

Computer-aided classification of colorectal segments during colonoscopy: a deep learning approach based on images of a magnetic endoscopic positioning device.

Scandinavian journal of gastroenterology
OBJECTIVE: Assessment of the anatomical colorectal segment of polyps during colonoscopy is important for treatment and follow-up strategies, but is largely operator dependent. This feasibility study aimed to assess whether, using images of a magnetic...

Application of convolutional neural networks for evaluating Helicobacter pylori infection status on the basis of endoscopic images.

Scandinavian journal of gastroenterology
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,...

Optical classification of neoplastic colorectal polyps - a computer-assisted approach (the COACH study).

Scandinavian journal of gastroenterology
BACKGROUND AND AIMS: Clinical data suggest that the quality of optical diagnoses of colorectal polyps differs markedly among endoscopists. The aim of this study was to develop a computer program that was able to differentiate neoplastic from non-neop...