AI Medical Compendium Journal:
Gastrointestinal endoscopy

Showing 51 to 60 of 104 articles

High performance in risk stratification of intraductal papillary mucinous neoplasms by confocal laser endomicroscopy image analysis with convolutional neural networks (with video).

Gastrointestinal endoscopy
BACKGROUND AND AIMS: EUS-guided needle-based confocal laser endomicroscopy (EUS-nCLE) can differentiate high-grade dysplasia/adenocarcinoma (HGD-Ca) in intraductal papillary mucinous neoplasms (IPMNs) but requires manual interpretation. We sought to ...

Identifying early gastric cancer under magnifying narrow-band images with deep learning: a multicenter study.

Gastrointestinal endoscopy
BACKGROUND AND AIMS: Narrow-band imaging with magnifying endoscopy (ME-NBI) has shown advantages in the diagnosis of early gastric cancer (EGC). However, proficiency in diagnostic algorithms requires substantial expertise and experience. In this stud...

Differential diagnosis for esophageal protruded lesions using a deep convolution neural network in endoscopic images.

Gastrointestinal endoscopy
BACKGROUND AND AIMS: Recent advances in deep convolutional neural networks (CNNs) have led to remarkable results in digestive endoscopy. In this study, we aimed to develop CNN-based models for the differential diagnosis of benign esophageal protruded...

Application of optical character recognition with natural language processing for large-scale quality metric data extraction in colonoscopy reports.

Gastrointestinal endoscopy
BACKGROUND AND AIMS: Colonoscopy is commonly performed for colorectal cancer screening in the United States. Reports are often generated in a non-standardized format and are not always integrated into electronic health records. Thus, this information...

Application of artificial intelligence using a novel EUS-based convolutional neural network model to identify and distinguish benign and malignant hepatic masses.

Gastrointestinal endoscopy
BACKGROUND AND AIMS: Detection and characterization of focal liver lesions (FLLs) is key for optimizing treatment for patients who may have a primary hepatic cancer or metastatic disease to the liver. This is the first study to develop an EUS-based c...