AI Medical Compendium Topic

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Intestine, Small

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Clinical usefulness of a deep learning-based system as the first screening on small-bowel capsule endoscopy reading.

Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society
BACKGROUND AND AIM: To examine whether our convolutional neural network (CNN) system based on deep learning can reduce the reading time of endoscopists without oversight of abnormalities in the capsule-endoscopy reading process.

Deep learning algorithms for automated detection of Crohn's disease ulcers by video capsule endoscopy.

Gastrointestinal endoscopy
BACKGROUND AND AIMS: The aim of our study was to develop and evaluate a deep learning algorithm for the automated detection of small-bowel ulcers in Crohn's disease (CD) on capsule endoscopy (CE) images of individual patients.

Automatic detection of blood content in capsule endoscopy images based on a deep convolutional neural network.

Journal of gastroenterology and hepatology
BACKGROUND AND AIM: Detecting blood content in the gastrointestinal tract is one of the crucial applications of capsule endoscopy (CE). The suspected blood indicator (SBI) is a conventional tool used to automatically tag images depicting possible ble...

Automatic detection and classification of protruding lesions in wireless capsule endoscopy images based on a deep convolutional neural network.

Gastrointestinal endoscopy
BACKGROUND AND AIMS: Protruding lesions of the small bowel vary in wireless capsule endoscopy (WCE) images, and their automatic detection may be difficult. We aimed to develop and test a deep learning-based system to automatically detect protruding l...

Automatic detection of various abnormalities in capsule endoscopy videos by a deep learning-based system: a multicenter study.

Gastrointestinal endoscopy
BACKGROUND AND AIMS: A deep convolutional neural network (CNN) system could be a high-level screening tool for capsule endoscopy (CE) reading but has not been established for targeting various abnormalities. We aimed to develop a CNN-based system and...

Improved classification and localization approach to small bowel capsule endoscopy using convolutional neural network.

Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society
BACKGROUND: Although great advances in artificial intelligence for interpreting small bowel capsule endoscopy (SBCE) images have been made in recent years, its practical use is still limited. The aim of this study was to develop a more practical conv...

Quantifying drug tissue biodistribution by integrating high content screening with deep-learning analysis.

Scientific reports
Quantitatively determining in vivo achievable drug concentrations in targeted organs of animal models and subsequent target engagement confirmation is a challenge to drug discovery and translation due to lack of bioassay technologies that can discrim...

Artificial intelligence and deep learning for small bowel capsule endoscopy.

Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society
Capsule endoscopy is ideally suited to artificial intelligence-based interpretation given its reliance on pattern recognition in still images. Time saving viewing modes and lesion detection features currently available rely on machine learning algori...

Artificial intelligence in small bowel capsule endoscopy - current status, challenges and future promise.

Journal of gastroenterology and hepatology
Neural network-based solutions are under development to alleviate physicians from the tedious task of small-bowel capsule endoscopy reviewing. Computer-assisted detection is a critical step, aiming to reduce reading times while maintaining accuracy. ...

Classification of intestinal T-cell receptor repertoires using machine learning methods can identify patients with coeliac disease regardless of dietary gluten status.

The Journal of pathology
In coeliac disease (CeD), immune-mediated small intestinal damage is precipitated by gluten, leading to variable symptoms and complications, occasionally including aggressive T-cell lymphoma. Diagnosis, based primarily on histopathological examinatio...