AIMC Topic: Endosonography

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Efficacy of endoscopic ultrasound with artificial intelligence for the diagnosis of gastrointestinal stromal tumors.

Journal of gastroenterology
BACKGROUND: Although endoscopic ultrasound (EUS) is reported to be suitable for determining the layer from which subepithelial lesions (SELs) originate, it is difficult to distinguish gastrointestinal stromal tumor (GIST) from non-GIST using only EUS...

Hierarchical Analysis of Factors Associated with T Staging of Gastric Cancer by Endoscopic Ultrasound.

Digestive diseases and sciences
BACKGROUND: Size, ulcer, differentiation, and location are known to be factors affecting the T stage accuracy of EUS in gastric cancer. However, whether an interaction exists among recognized variables is poorly understood. The aim of this study was ...

Detecting vulnerable plaque with vulnerability index based on convolutional neural networks.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Plaque rupture and subsequent thrombosis are major processes of acute cardiovascular events. The Vulnerability Index is a very important indicator of whether a plaque is ruptured, and these easily ruptured or fragile plaques can be detected early. Th...

Response to repeat echoendoscopic celiac plexus neurolysis in pancreatic cancer patients: A machine learning approach.

Pancreatology : official journal of the International Association of Pancreatology (IAP) ... [et al.]
BACKGROUND: /Objectives: Efficacy of repeat echoendoscopic celiac plexus neurolysis is still unclear. Aim of the study was to assess the efficacy of repeat celiac plexus neurolysis and to build an artificial neural network model able to predict pain ...

Artificial intelligence-assisted endobronchial ultrasound for differentiating between benign and malignant thoracic lymph nodes: a meta-analysis.

BMC pulmonary medicine
BACKGROUND: Endobronchial ultrasound (EBUS) is a widely used imaging modality for evaluating thoracic lymph nodes (LNs), particularly in the staging of lung cancer. Artificial intelligence (AI)-assisted EBUS has emerged as a promising tool to enhance...

Artificial intelligence and endoanal ultrasound: pioneering automated differentiation of benign anal and sphincter lesions.

Techniques in coloproctology
BACKGROUND: Anal injuries, such as lacerations and fissures, are challenging to diagnose because of their anatomical complexity. Endoanal ultrasound (EAUS) has proven to be a reliable tool for detailed visualization of anal structures but relies on e...

Artificial intelligence-assisted endoscopic ultrasound diagnosis of esophageal subepithelial lesions.

Surgical endoscopy
BACKGROUND: Endoscopic ultrasound (EUS) is one of the most accurate methods for determining the originating layer of subepithelial lesions (SELs). However, the accuracy is greatly influenced by the expertise and proficiency of the endoscopist. In thi...

Characterization of subepithelial tumors of upper gastrointestinal tract by endoscopic ultrasound.

World journal of gastroenterology
In this article we comment on the paper by Xu describing retrospective data on endoscopic treatment outcome of esophageal gastrointestinal stromal tumors (GISTs). Esophageal GIST is a rare type of mesenchymal tumor. GISTs originate from the intersti...

Advancements in biliopancreatic endoscopy - A comprehensive review of artificial intelligence in EUS and ERCP.

Revista espanola de enfermedades digestivas
The development and implementation of artificial intelligence (AI), particularly deep learning (DL) models, has generated significant interest across various fields of gastroenterology. While research in luminal endoscopy has seen rapid translation t...