A comprehensive screening method using machine learning and many factors (biological characteristics, Helicobacter pylori infection status, endoscopic findings and blood test results), accumulated daily as data in hospitals, could improve the accurac...
Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society
Aug 22, 2019
The latest state of the art technological innovations have led to a palpable progression in endoscopic imaging and may facilitate standardisation of practice. One of the most rapidly evolving modalities is artificial intelligence with recent studies ...
BACKGROUND AND AIMS: Few artificial intelligence-based technologies have been developed to improve the efficiency of screening for esophageal squamous cell carcinoma (ESCC). Here, we developed and validated a novel system of computer-aided detection ...
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...
The Journal of international medical research
Mar 26, 2019
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.
Scandinavian journal of gastroenterology
Mar 17, 2019
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,...
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...
IEEE transactions on bio-medical engineering
Dec 27, 2018
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...
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