AIMC Topic: Endoscopy, Gastrointestinal

Clear Filters Showing 41 to 50 of 159 articles

Framework and metrics for the clinical use and implementation of artificial intelligence algorithms into endoscopy practice: recommendations from the American Society for Gastrointestinal Endoscopy Artificial Intelligence Task Force.

Gastrointestinal endoscopy
In the past few years, we have seen a surge in the development of relevant artificial intelligence (AI) algorithms addressing a variety of needs in GI endoscopy. To accept AI algorithms into clinical practice, their effectiveness, clinical value, and...

Role of artificial intelligence-guided esophagogastroduodenoscopy in assessing the procedural completeness and quality.

Indian journal of gastroenterology : official journal of the Indian Society of Gastroenterology
BACKGROUND AND AIMS: The quality of esophagogastroduodenoscopy (EGD) can have great impact on the detection of esophageal and gastric lesions, including malignancies. The aim of the study is to investigate the use of artificial intelligence (AI) duri...

Deep-Learning and Device-Assisted Enteroscopy: Automatic Panendoscopic Detection of Ulcers and Erosions.

Medicina (Kaunas, Lithuania)
: Device-assisted enteroscopy (DAE) has a significant role in approaching enteric lesions. Endoscopic observation of ulcers or erosions is frequent and can be associated with many nosological entities, namely Crohn's disease. Although the application...

Detection of duodenal villous atrophy on endoscopic images using a deep learning algorithm.

Gastrointestinal endoscopy
BACKGROUND AND AIMS: Celiac disease with its endoscopic manifestation of villous atrophy (VA) is underdiagnosed worldwide. The application of artificial intelligence (AI) for the macroscopic detection of VA at routine EGD may improve diagnostic perfo...

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...

A deep-learning based system using multi-modal data for diagnosing gastric neoplasms in real-time (with video).

Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association
BACKGROUND: White light (WL) and weak-magnifying (WM) endoscopy are both important methods for diagnosing gastric neoplasms. This study constructed a deep-learning system named ENDOANGEL-MM (multi-modal) aimed at real-time diagnosing gastric neoplasm...

Improving quality control in the routine practice for histopathological interpretation of gastrointestinal endoscopic biopsies using artificial intelligence.

PloS one
BACKGROUND: Colorectal and gastric cancer are major causes of cancer-related deaths. In Korea, gastrointestinal (GI) endoscopic biopsy specimens account for a high percentage of histopathologic examinations. Lack of a sufficient pathologist workforce...

Artificial intelligence and automation in endoscopy and surgery.

Nature reviews. Gastroenterology & hepatology
Modern endoscopy relies on digital technology, from high-resolution imaging sensors and displays to electronics connecting configurable illumination and actuation systems for robotic articulation. In addition to enabling more effective diagnostic and...

Vessel and tissue recognition during third-space endoscopy using a deep learning algorithm.

Gut
In this study, we aimed to develop an artificial intelligence clinical decision support solution to mitigate operator-dependent limitations during complex endoscopic procedures such as endoscopic submucosal dissection and peroral endoscopic myotomy, ...