AIMC Topic: Colonic Polyps

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Polyp detection algorithm can detect small polyps: Ex vivo reading test compared with endoscopists.

Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society May 28, 2020
BACKGROUND AND STUDY AIMS: Small polyps are occasionally missed during colonoscopy. This study was conducted to validate the diagnostic performance of a polyp-detection algorithm to alert endoscopists to unrecognized lesions.
Deep Learning Colonic Polyps Adenomatous Polyps Humans Algorithms Colonoscopy
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The impact of deep convolutional neural network-based artificial intelligence on colonoscopy outcomes: A systematic review with meta-analysis.

Journal of gastroenterology and hepatology Apr 26, 2020
BACKGROUND AND AIM: The utility of artificial intelligence (AI) in colonoscopy has gained popularity in current times. Recent trials have evaluated the efficacy of deep convolutional neural network (DCNN)-based AI system in colonoscopy for improving ...
Humans Mass Screening Adenoma Neural Networks, Computer Colonic Neoplasms Artificial Intelligence Colonic Polyps Colonoscopy
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Evaluation of a Deep Neural Network for Automated Classification of Colorectal Polyps on Histopathologic Slides.

JAMA network open Apr 1, 2020
IMPORTANCE: Histologic classification of colorectal polyps plays a critical role in screening for colorectal cancer and care of affected patients. An accurate and automated algorithm for the classification of colorectal polyps on digitized histopatho...
Humans Neural Networks, Computer Image Interpretation, Computer-Assisted Algorithms Histocytochemistry Sensitivity and Specificity Deep Learning Colonic Polyps
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Improved Accuracy in Optical Diagnosis of Colorectal Polyps Using Convolutional Neural Networks with Visual Explanations.

Gastroenterology Feb 29, 2020
BACKGROUND & AIMS: Narrow-band imaging (NBI) can be used to determine whether colorectal polyps are adenomatous or hyperplastic. We investigated whether an artificial intelligence (AI) system can increase the accuracy of characterizations of polyps b...
Workflow Colonic Polyps Image Interpretation, Computer-Assisted Deep Learning Clinical Competence Predictive Value of Tests Seoul Adenomatous Polyps Narrow Band Imaging Observer Variation Hyperplasia Visual Perception Humans Colonoscopy Diagnosis, Computer-Assisted Reproducibility of Results Colorectal Neoplasms
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Polyp fingerprint: automatic recognition of colorectal polyps' unique features.

Surgical endoscopy Feb 11, 2020
BACKGROUND: Content-based image retrieval (CBIR) is an application of machine learning used to retrieve images by similarity on the basis of features. Our objective was to develop a CBIR system that could identify images containing the same polyp ('p...
Humans Image Interpretation, Computer-Assisted Machine Learning Information Storage and Retrieval Colonoscopy Colonic Polyps
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Effect of a deep-learning computer-aided detection system on adenoma detection during colonoscopy (CADe-DB trial): a double-blind randomised study.

The lancet. Gastroenterology & hepatology Jan 22, 2020
BACKGROUND: Colonoscopy with computer-aided detection (CADe) has been shown in non-blinded trials to improve detection of colon polyps and adenomas by providing visual alarms during the procedure. We aimed to assess the effectiveness of a CADe system...
Adult Colorectal Neoplasms Male Case-Control Studies Diagnosis, Computer-Assisted Middle Aged Colonoscopy Humans Female Colonic Polyps Observer Variation Mass Screening Early Diagnosis Adenoma Deep Learning Clinical Alarms Double-Blind Method China Incidence
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Endoscopic diagnosis and treatment planning for colorectal polyps using a deep-learning model.

Scientific reports Jan 8, 2020
We aimed to develop a computer-aided diagnostic system (CAD) for predicting colorectal polyp histology using deep-learning technology and to validate its performance. Near-focus narrow-band imaging (NBI) pictures of colorectal polyps were retrieved f...
Colonic Polyps Narrow Band Imaging Models, Statistical Adenoma Artificial Intelligence Endoscopy, Gastrointestinal Colonoscopy Retrospective Studies Diagnosis, Computer-Assisted Humans Deep Learning
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Use of Endoscopic Impression, Artificial Intelligence, and Pathologist Interpretation to Resolve Discrepancies Between Endoscopy and Pathology Analyses of Diminutive Colorectal Polyps.

Gastroenterology Dec 18, 2019
Optical Imaging Adenoma Colonic Polyps Image Interpretation, Computer-Assisted Artificial Intelligence Humans Decision Support Techniques Colorectal Neoplasms Colonoscopy
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An overview of deep learning algorithms and water exchange in colonoscopy in improving adenoma detection.

Expert review of gastroenterology & hepatology Nov 30, 2019
: Among the Gastrointestinal (GI) Endoscopy Editorial Board top 10 topics in advances in endoscopy in 2018, water exchange colonoscopy and artificial intelligence were both considered important advances. Artificial intelligence holds the potential to...
Predictive Value of Tests Colonic Neoplasms Colonic Polyps Reproducibility of Results Diagnosis, Computer-Assisted Image Interpretation, Computer-Assisted Humans Colonoscopy Deep Learning Adenomatous Polyps Water
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Uncertainty and interpretability in convolutional neural networks for semantic segmentation of colorectal polyps.

Medical image analysis Nov 20, 2019
Colorectal polyps are known to be potential precursors to colorectal cancer, which is one of the leading causes of cancer-related deaths on a global scale. Early detection and prevention of colorectal cancer is primarily enabled through manual screen...
Image Interpretation, Computer-Assisted Colonoscopy Humans Uncertainty Semantics Neural Networks, Computer Deep Learning Monte Carlo Method Decision Support Techniques Colonic Polyps
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