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Endoscopy, Gastrointestinal

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Comparative study of convolutional neural network architectures for gastrointestinal lesions classification.

PeerJ
The gastrointestinal (GI) tract can be affected by different diseases or lesions such as esophagitis, ulcers, hemorrhoids, and polyps, among others. Some of them can be precursors of cancer such as polyps. Endoscopy is the standard procedure for the ...

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...

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...

Deep learning-based clinical decision support system for gastric neoplasms in real-time endoscopy: development and validation study.

Endoscopy
BACKGROUND : Deep learning models have previously been established to predict the histopathology and invasion depth of gastric lesions using endoscopic images. This study aimed to establish and validate a deep learning-based clinical decision support...

Transformer-based multi-task learning for classification and segmentation of gastrointestinal tract endoscopic images.

Computers in biology and medicine
Despite being widely utilized to help endoscopists identify gastrointestinal (GI) tract diseases using classification and segmentation, models based on convolutional neural network (CNN) have difficulties in distinguishing the similarities among some...

Artificial Intelligence in Pediatric Endoscopy: Current Status and Future Applications.

Gastrointestinal endoscopy clinics of North America
The application of artificial intelligence (AI) has great promise for improving pediatric endoscopy. The majority of preclinical studies have been undertaken in adults, with the greatest progress being made in the context of colorectal cancer screeni...

[Colorectal cancer: technological revolution].

Revue medicale suisse
Colorectal cancer represents 4500 incidental cases in Switzerland per year, with an incidence increasing among the youngest patients. Technological innovation guides the management of colorectal cancer. Artificial intelligence in endoscopy optimizes ...

Artificial Intelligence in Inflammatory Bowel Disease Endoscopy: Implications for Clinical Trials.

Journal of Crohn's & colitis
Artificial intelligence shows promise for clinical research in inflammatory bowel disease endoscopy. Accurate assessment of endoscopic activity is important in clinical practice and inflammatory bowel disease clinical trials. Emerging artificial inte...