AIMC Topic: Gastrointestinal Tract

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Addressing the Contrast Media Recognition Challenge: A Fully Automated Machine Learning Approach for Predicting Contrast Phases in CT Imaging.

Investigative radiology
OBJECTIVES: Accurately acquiring and assigning different contrast-enhanced phases in computed tomography (CT) is relevant for clinicians and for artificial intelligence orchestration to select the most appropriate series for analysis. However, this i...

Advancing Artificial Intelligence Integration Into the Pathology Workflow: Exploring Opportunities in Gastrointestinal Tract Biopsies.

Laboratory investigation; a journal of technical methods and pathology
This review aims to present a comprehensive overview of the current landscape of artificial intelligence (AI) applications in the analysis of tubular gastrointestinal biopsies. These publications cover a spectrum of conditions, ranging from inflammat...

Ethical Implications of Artificial Intelligence in Gastroenterology.

Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association

Untethered shape-changing devices in the gastrointestinal tract.

Expert opinion on drug delivery
INTRODUCTION: Advances in microfabrication, automation, and computer engineering seek to revolutionize small-scale devices and machines. Emerging trends in medicine point to smart devices that emulate the motility, biosensing abilities, and intellige...

The Evolving Role of Artificial Intelligence in Gastrointestinal Histopathology: An Update.

Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association
Significant advances in artificial intelligence (AI) over the past decade potentially may lead to dramatic effects on clinical practice. Digitized histology represents an area ripe for AI implementation. We describe several current needs within the w...

Smart capsules for sensing and sampling the gut: status, challenges and prospects.

Gut
Smart capsules are developing at a tremendous pace with a promise to become effective clinical tools for the diagnosis and monitoring of gut health. This field emerged in the early 2000s with a successful translation of an endoscopic capsule from lab...

Gastrointestinal tract disorders classification using ensemble of InceptionNet and proposed GITNet based deep feature with ant colony optimization.

PloS one
Computer-aided classification of diseases of the gastrointestinal tract (GIT) has become a crucial area of research. Medical science and artificial intelligence have helped medical experts find GIT diseases through endoscopic procedures. Wired endosc...

Prediction of gastrointestinal functional state based on myoelectric recordings utilizing a deep neural network architecture.

PloS one
Functional and motility-related gastrointestinal (GI) disorders affect nearly 40% percent of the population. Disturbances of GI myoelectric activity have been proposed to play a significant role in these disorders. A significant barrier to usage of t...