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Celiac Disease

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Quantitative analysis of patients with celiac disease by video capsule endoscopy: A deep learning method.

Computers in biology and medicine
BACKGROUND: Celiac disease is one of the most common diseases in the world. Capsule endoscopy is an alternative way to visualize the entire small intestine without invasiveness to the patient. It is useful to characterize celiac disease, but hours ar...

Machine Learning in Detection of Undiagnosed Celiac Disease.

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

Automated classification of celiac disease during upper endoscopy: Status quo and quo vadis.

Computers in biology and medicine
A large amount of digital image material is routinely captured during esophagogastroduodenoscopies but, for the most part, is not used for confirming the diagnosis process of celiac disease which is primarily based on histological examination of biop...

Versatility of fuzzy logic in chronic diseases: A review.

Medical hypotheses
The review aims at providing current state of evidence in the field of medicine with fuzzy logic for diagnosing diseases. Literature reveals that fuzzy logic has been used effectively in medicine. Different types of methodologies have been applied to...

Overview of Deep Learning in Gastrointestinal Endoscopy.

Gut and liver
Artificial intelligence is likely to perform several roles currently performed by humans, and the adoption of artificial intelligence-based medicine in gastroenterology practice is expected in the near future. Medical image-based diagnoses, such as p...

Physician Review of a Celiac Disease Risk Estimation and Decision-Making Expert System.

Journal of the American College of Nutrition
Celiac disease is a genetic disease affecting people of all ages, resulting in small intestine enteropathy. It is considered to be a clinical chameleon. Average prevalence of celiac disease is 1 out of 100 people with data indicating the risk may be...

Automatic classification of IgA endomysial antibody test for celiac disease: a new method deploying machine learning.

Scientific reports
Widespread use of endomysial autoantibody (EmA) test in diagnostics of celiac disease is limited due to its subjectivity and its requirement of an expert evaluator. The study aimed to determine whether machine learning can be applied to create a new ...

Assessment of Machine Learning Detection of Environmental Enteropathy and Celiac Disease in Children.

JAMA network open
IMPORTANCE: Duodenal biopsies from children with enteropathies associated with undernutrition, such as environmental enteropathy (EE) and celiac disease (CD), display significant histopathological overlap.