AIMC Topic: Stomach Neoplasms
Clear Filters Showing 261 to 270 of 439 articles
A Medical Decision Support System to Assess Risk Factors for Gastric Cancer Based on Fuzzy Cognitive Map.
Computational and mathematical methods in medicine
Oct 5, 2020
Gastric cancer (GC), one of the most common cancers around the world, is a multifactorial disease and there are many risk factors for this disease. Assessing the risk of GC is essential for choosing an appropriate healthcare strategy. There have been...
A deep learning-based system for identifying differentiation status and delineating the margins of early gastric cancer in magnifying narrow-band imaging endoscopy.
Endoscopy
Sep 29, 2020
BACKGROUND : Accurate identification of the differentiation status and margins for early gastric cancer (EGC) is critical for determining the surgical strategy and achieving curative resection in EGC patients. The aim of this study was to develop a r...
An invited commentary on "Robotic versus laparoscopic gastrectomy for gastric cancer: The largest meta-analysis".
International journal of surgery (London, England)
Sep 25, 2020
CT-based deep learning radiomics analysis for evaluation of serosa invasion in advanced gastric cancer.
European journal of radiology
Sep 11, 2020
PURPOSE: This work aimed to develop and validate a deep learning radiomics model for evaluating serosa invasion in gastric cancer.
Clinically applicable histopathological diagnosis system for gastric cancer detection using deep learning.
Nature communications
Aug 27, 2020
The early detection and accurate histopathological diagnosis of gastric cancer increase the chances of successful treatment. The worldwide shortage of pathologists offers a unique opportunity for the use of artificial intelligence assistance systems ...
Challenging detection of hard-to-find gastric cancers with artificial intelligence-assisted endoscopy.
Gut
Aug 18, 2020
Anatomical classification of upper gastrointestinal organs under various image capture conditions using AlexNet.
Computers in biology and medicine
Aug 7, 2020
BACKGROUND: Machine learning has led to several endoscopic studies about the automated localization of digestive lesions and prediction of cancer invasion depth. Training and validation dataset collection are required for a disease in each digestive ...
Application of artificial intelligence using a convolutional neural network for diagnosis of early gastric cancer based on magnifying endoscopy with narrow-band imaging.
Journal of gastroenterology and hepatology
Jul 28, 2020
BACKGROUND AND AIM: Magnifying endoscopy with narrow-band imaging (ME-NBI) has made a huge contribution to clinical practice. However, acquiring skill at ME-NBI diagnosis of early gastric cancer (EGC) requires considerable expertise and experience. R...
Development and validation of an artificial neural network prognostic model after gastrectomy for gastric carcinoma: An international multicenter cohort study.
Cancer medicine
Jul 15, 2020
BACKGROUND: Recently, artificial neural network (ANN) methods have also been adopted to deal with the complex multidimensional nonlinear relationship between clinicopathologic variables and survival for patients with gastric cancer. Using a multinati...
How can endoscopists adapt and collaborate with artificial intelligence for early gastric cancer detection?
Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society
Jun 29, 2020
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