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Gastrointestinal Tract

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Robotics in flexible endoscopy: current status and future prospects.

Current opinion in gastroenterology
PURPOSE OF REVIEW: Advanced endoscopy procedures are technically challenging and require extensive training. Recent technological advances made in computer science and robotics have the potential to enhance the performance of complex intraluminal and...

A systematic evaluation and optimization of automatic detection of ulcers in wireless capsule endoscopy on a large dataset using deep convolutional neural networks.

Physics in medicine and biology
Compared with conventional gastroscopy which is invasive and painful, wireless capsule endoscopy (WCE) can provide noninvasive examination of gastrointestinal (GI) tract. The WCE video can effectively support physicians to reach a diagnostic decision...

MAPGI: Accurate identification of anatomical landmarks and diseased tissue in gastrointestinal tract using deep learning.

Computers in biology and medicine
Automatic detection of anatomical landmarks and diseases in medical images is a challenging task which could greatly aid medical diagnosis and reduce the cost and time of investigational procedures. Also, two particular challenges of digital image pr...

Appetite ratings of foods are predictable with an in vitro advanced gastrointestinal model in combination with an in silico artificial neural network.

Food research international (Ottawa, Ont.)
The expected increase of global obesity prevalence makes it necessary to have information about the effects of meal intakes on the feeling of appetite. Because human clinical studies are time and cost intensive, there is a need for a reliable alterna...

Investigation of Current Control for a New Bi-directional Linear Capsule Robot.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
In this paper, a bi-directional linear capsule robot (capsulbot) for potential applications in Gastrointestinal (GI) tract inside human body is studied. Compared with the conventional endoscope limited by its poor locomotion and steering capabilities...

Predictive Tilt Compensation for Robot Assisted Magnetic Capsule Endoscope.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Wireless capsule endoscopes provide a painless and non-invasive alternative to the flexible endoscope in various applications of the gastrointestinal tract diagnosis. Operating a wireless capsule endoscope in the colon may benefit from an active posi...

A Novel Relative Position Estimation Method for Capsule Robot Moving in Gastrointestinal Tract.

Sensors (Basel, Switzerland)
Recently, a variety of positioning and tracking methods have been proposed for capsule robots moving in the gastrointestinal (GI) tract to provide real-time unobstructed spatial pose results. However, the current absolute position-based result cannot...

Absorption and biotransformation of four compounds in the Guizhi decoction in the gastrointestinal tracts of rats.

Journal of traditional Chinese medicine = Chung i tsa chih ying wen pan
OBJECTIVE: To study the absorption and biotransformation of liquiritin, cinnamic acid, paeoniflorin, and glycyrrhizic acid in the Guizhi decoction (GZD) in the gastrointestinal tracts of rats.

Application of artificial intelligence in gastroenterology.

World journal of gastroenterology
Artificial intelligence (AI) using deep-learning (DL) has emerged as a breakthrough computer technology. By the era of big data, the accumulation of an enormous number of digital images and medical records drove the need for the utilization of AI to ...

Functional brain networks and neuroanatomy underpinning nausea severity can predict nausea susceptibility using machine learning.

The Journal of physiology
KEY POINTS: Nausea is an adverse experience characterised by alterations in autonomic and cerebral function. Susceptibility to nausea is difficult to predict, but machine learning has yet to be applied to this field of study. The severity of nausea t...