AIMC Topic: Adenomatous Polyps

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Real-time gastric polyp detection using convolutional neural networks.

PloS one Mar 25, 2019
Computer-aided polyp detection in gastric gastroscopy has been the subject of research over the past few decades. However, despite significant advances, automatic polyp detection in real time is still an unsolved problem. In this paper, we report on ...
Female Stomach Neoplasms Humans Neural Networks, Computer Gastroscopy Adenomatous Polyps Male Image Processing, Computer-Assisted
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Deep Learning Localizes and Identifies Polyps in Real Time With 96% Accuracy in Screening Colonoscopy.

Gastroenterology Jun 18, 2018
BACKGROUND & AIMS: The benefit of colonoscopy for colorectal cancer prevention depends on the adenoma detection rate (ADR). The ADR should reflect the adenoma prevalence rate, which is estimated to be higher than 50% in the screening-age population. ...
Reproducibility of Results Colorectal Neoplasms Machine Learning Prognosis ROC Curve Early Detection of Cancer Colonoscopy Diagnosis, Computer-Assisted Humans Neural Networks, Computer Video Recording Feasibility Studies Observer Variation Predictive Value of Tests Image Interpretation, Computer-Assisted Area Under Curve Colonic Polyps Adenomatous Polyps
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Natural Language Processing Accurately Calculates Adenoma and Sessile Serrated Polyp Detection Rates.

Digestive diseases and sciences Apr 26, 2018
BACKGROUND: ADR is a widely used colonoscopy quality indicator. Calculation of ADR is labor-intensive and cumbersome using current electronic medical databases. Natural language processing (NLP) is a method used to extract meaning from unstructured o...
Automation Adenomatous Polyps Colonic Polyps Quality Indicators, Health Care Natural Language Processing Colonic Neoplasms Colonoscopy Early Detection of Cancer Reproducibility of Results Adenocarcinoma Electronic Health Records Predictive Value of Tests Humans Female Male
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Real-time differentiation of adenomatous and hyperplastic diminutive colorectal polyps during analysis of unaltered videos of standard colonoscopy using a deep learning model.

Gut Oct 24, 2017
BACKGROUND: In general, academic but not community endoscopists have demonstrated adequate endoscopic differentiation accuracy to make the 'resect and discard' paradigm for diminutive colorectal polyps workable. Computer analysis of video could poten...
Video Recording Adenomatous Polyps Predictive Value of Tests Clinical Competence Narrow Band Imaging Colonic Polyps Humans Colonoscopy Diagnosis, Differential Sensitivity and Specificity Deep Learning
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A hierarchical classifier based on human blood plasma fluorescence for non-invasive colorectal cancer screening.

Artificial intelligence in medicine Sep 20, 2017
Colorectal cancer (CRC) a leading cause of death by cancer, and screening programs for its early identification are at the heart of the increasing survival rates. To motivate population participation, non-invasive, accurate, scalable and cost-effecti...
Colonic Polyps Predictive Value of Tests Biomarkers, Tumor Adenomatous Polyps Case-Control Studies Spectrometry, Fluorescence Humans Support Vector Machine Reproducibility of Results Early Detection of Cancer Colorectal Neoplasms
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