AI Medical Compendium Topic

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Endoscopy, Gastrointestinal

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Artificial intelligence and the future of endoscopy.

Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society

An artificial neural network model for prediction of hypoxemia during sedation for gastrointestinal endoscopy.

The Journal of international medical research
OBJECTIVE: This study was designed to assess clinical predictors of hypoxemia and develop an artificial neural network (ANN) model for prediction of hypoxemia during sedation for gastrointestinal endoscopy examination.

Application of convolutional neural networks for evaluating Helicobacter pylori infection status on the basis of endoscopic images.

Scandinavian journal of gastroenterology
BACKGROUND AND AIM: We recently reported the role of artificial intelligence in the diagnosis of Helicobacter pylori (H. pylori) gastritis on the basis of endoscopic images. However, that study included only H. pylori-positive and -negative patients,...

Spotting malignancies from gastric endoscopic images using deep learning.

Surgical endoscopy
BACKGROUND: Gastric cancer is a common kind of malignancies, with yearly occurrences exceeding one million worldwide in 2017. Typically, ulcerous and cancerous tissues develop abnormal morphologies through courses of progression. Endoscopy is a routi...

Reliable Label-Efficient Learning for Biomedical Image Recognition.

IEEE transactions on bio-medical engineering
The use of deep neural networks for biomedical image analysis requires a sufficient number of labeled datasets. To acquire accurate labels as the gold standard, multiple observers with specific expertise are required for both annotation and proofread...

Application of artificial intelligence using a convolutional neural network for detecting gastric cancer in endoscopic images.

Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association
BACKGROUND: Image recognition using artificial intelligence with deep learning through convolutional neural networks (CNNs) has dramatically improved and been increasingly applied to medical fields for diagnostic imaging. We developed a CNN that can ...

Identification of lesion images from gastrointestinal endoscope based on feature extraction of combinational methods with and without learning process.

Medical image analysis
The gastrointestinal endoscopy in this study refers to conventional gastroscopy and wireless capsule endoscopy (WCE). Both of these techniques produce a large number of images in each diagnosis. The lesion detection done by hand from the images above...

Gastroesophageal Reflux Disease Diagnosis Using Hierarchical Heterogeneous Descriptor Fusion Support Vector Machine.

IEEE transactions on bio-medical engineering
A new computer-aided diagnosis method is proposed to diagnose the gastroesophageal reflux disease (GERD) from endoscopic images of the esophageal-gastric junction. To avoid the interferences of different endoscope devices and automatic camera white b...

Evaluation of a novel flexible snake robot for endoluminal surgery.

Surgical endoscopy
BACKGROUND: Endoluminal therapeutic procedures such as endoscopic submucosal dissection are increasingly attractive given the shift in surgical paradigm towards minimally invasive surgery. This novel three-channel articulated robot was developed to o...