AIMC Topic: Endosonography
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Artificial intelligence-assisted endobronchial ultrasound for differentiating between benign and malignant thoracic lymph nodes: a meta-analysis.
BMC pulmonary medicine
Jul 2, 2025
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...
Can intraoperative improvement of radial endobronchial ultrasound imaging enhance the diagnostic yield in peripheral pulmonary lesions?
BMC pulmonary medicine
May 26, 2025
BACKGROUND: Data regarding the diagnostic efficacy of radial endobronchial ultrasound (R-EBUS) findings obtained via transbronchial needle aspiration (TBNA)/biopsy (TBB) with endobronchial ultrasonography with a guide sheath (EBUS-GS) for peripheral ...
An artificial intelligence model utilizing endoscopic ultrasonography for differentiating small and micro gastric stromal tumors from gastric leiomyomas.
BMC gastroenterology
Apr 9, 2025
BACKGROUND: Gastric stromal tumors (GSTs) and gastric leiomyomas (GLs) represent the primary subtypes of gastric submucosal tumors (SMTs) characterized by distinct biological characteristics and treatment modalities. The accurate differentiation betw...
Prediction of Lymph Node Metastasis in Lung Cancer Using Deep Learning of Endobronchial Ultrasound Images With Size on CT and PET-CT Findings.
Respirology (Carlton, Vic.)
Mar 3, 2025
BACKGROUND AND OBJECTIVE: Echo features of lymph nodes (LNs) influence target selection during endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA). This study evaluates deep learning's diagnostic capabilities on EBUS images f...
An endoscopic ultrasound-based interpretable deep learning model and nomogram for distinguishing pancreatic neuroendocrine tumors from pancreatic cancer.
Scientific reports
Jan 27, 2025
To retrospectively develop and validate an interpretable deep learning model and nomogram utilizing endoscopic ultrasound (EUS) images to predict pancreatic neuroendocrine tumors (PNETs). Following confirmation via pathological examination, a retrosp...
The Role of Artificial Intelligence for Advanced Endoscopy.
Gastrointestinal endoscopy clinics of North America
Jan 18, 2025
Artificial intelligence (AI) application in gastroenterology has grown in the last decade and continues to evolve very rapidly. Early promising results have opened the door to explore its potential application to advanced endoscopy (AE). The aim of t...
Endoscopic ultrasonography-based intratumoral and peritumoral machine learning ultrasomics model for predicting the pathological grading of pancreatic neuroendocrine tumors.
BMC medical imaging
Jan 18, 2025
OBJECTIVES: The objective is to develop and validate intratumoral and peritumoral ultrasomics models utilizing endoscopic ultrasonography (EUS) to predict pathological grading in pancreatic neuroendocrine tumors (PNETs).
Integrating artificial intelligence with endoscopic ultrasound in the early detection of bilio-pancreatic lesions: Current advances and future prospects.
Best practice & research. Clinical gastroenterology
Jan 4, 2025
The integration of Artificial Intelligence (AI) in endoscopic ultrasound (EUS) represents a transformative advancement in the early detection and management of biliopancreatic lesions. This review highlights the current state of AI-enhanced EUS (AI-E...
Artificial intelligence in pancreaticobiliary endoscopy: Current applications and future directions.
Journal of digestive diseases
Dec 30, 2024
Pancreaticobiliary endoscopy is an essential tool for diagnosing and treating pancreaticobiliary diseases. However, it does not fully meet clinical needs, which presents challenges such as significant difficulty in operation and risks of missed diagn...
Role of Artificial Intelligence for Endoscopic Ultrasound.
Gastrointestinal endoscopy clinics of North America
Dec 27, 2024
Endoscopic ultrasound (EUS) is widely used for the diagnosis of biliopancreatic and gastrointestinal tract diseases, but it is one of the most operator-dependent endoscopic techniques, requiring a long and complex learning curve. The role of artifici...
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