AIMC Topic: Colonic Polyps
Clear Filters Showing 31 to 40 of 171 articles
Colonoscopy polyp classification via enhanced scattering wavelet Convolutional Neural Network.
PloS one
Oct 11, 2024
Among the most common cancers, colorectal cancer (CRC) has a high death rate. The best way to screen for colorectal cancer (CRC) is with a colonoscopy, which has been shown to lower the risk of the disease. As a result, Computer-aided polyp classific...
Effectiveness of artificial intelligence assisted colonoscopy on adenoma and polyp miss rate: A meta-analysis of tandem RCTs.
Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver
Sep 24, 2024
BACKGROUND AND AIMS: One-fourth of colorectal neoplasia is missed at screening colonoscopy, representing the leading cause of interval colorectal cancer (I-CRC). This systematic review and meta-analysis summarizes the efficacy of computer-aided colon...
Polyp detection with colonoscopy assisted by the GI Genius artificial intelligence endoscopy module compared with standard colonoscopy in routine colonoscopy practice (COLO-DETECT): a multicentre, open-label, parallel-arm, pragmatic randomised controlled trial.
The lancet. Gastroenterology & hepatology
Aug 14, 2024
BACKGROUND: Increased polyp detection during colonoscopy is associated with decreased post-colonoscopy colorectal cancer incidence and mortality. The COLO-DETECT trial aimed to assess the clinical effectiveness of the GI Genius intelligent endoscopy ...
AI support for colonoscopy quality control using CNN and transformer architectures.
BMC gastroenterology
Aug 9, 2024
BACKGROUND: Construct deep learning models for colonoscopy quality control using different architectures and explore their decision-making mechanisms.
PolypNextLSTM: a lightweight and fast polyp video segmentation network using ConvNext and ConvLSTM.
International journal of computer assisted radiology and surgery
Aug 8, 2024
PURPOSE: Commonly employed in polyp segmentation, single-image UNet architectures lack the temporal insight clinicians gain from video data in diagnosing polyps. To mirror clinical practices more faithfully, our proposed solution, PolypNextLSTM, leve...
Appropriate trust in artificial intelligence for the optical diagnosis of colorectal polyps: the role of human/artificial intelligence interaction.
Gastrointestinal endoscopy
Jun 26, 2024
BACKGROUND AND AIMS: Computer-aided diagnosis (CADx) for the optical diagnosis of colorectal polyps is thoroughly investigated. However, studies on human-artificial intelligence interaction are lacking. Our aim was to investigate endoscopists' trust ...
Visual explanations for polyp detection: How medical doctors assess intrinsic versus extrinsic explanations.
PloS one
May 31, 2024
Deep learning has achieved immense success in computer vision and has the potential to help physicians analyze visual content for disease and other abnormalities. However, the current state of deep learning is very much a black box, making medical pr...
Artificial Intelligence for Real-Time Prediction of the Histology of Colorectal Polyps by General Endoscopists.
Annals of internal medicine
May 21, 2024
BACKGROUND: Real-time prediction of histologic features of small colorectal polyps may prevent resection and/or pathologic evaluation and therefore decrease colonoscopy costs. Previous studies showed that computer-aided diagnosis (CADx) was highly ac...
Artificial intelligence for dysplasia detection during surveillance colonoscopy in patients with ulcerative colitis: A cross-sectional, non-inferiority, diagnostic test comparison study.
Gastroenterologia y hepatologia
May 11, 2024
BACKGROUND AND STUDY AIM: High-definition virtual chromoendoscopy, along with targeted biopsies, is recommended for dysplasia surveillance in ulcerative colitis patients at risk for colorectal cancer. Computer-aided detection (CADe) systems aim to im...
Establishment and validation of an artificial intelligence-based model for real-time detection and classification of colorectal adenoma.
Scientific reports
May 10, 2024
Colorectal cancer (CRC) prevention requires early detection and removal of adenomas. We aimed to develop a computational model for real-time detection and classification of colorectal adenoma. Computationally constrained background based on real-time...
Don't Miss the Future of Medicine
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 31964
- Neural Networks, Computer 30201
- Algorithms 27375
- Deep Learning 26880
- Artificial Intelligence 24818
- Robotics 13382
- Image Processing, Computer-Assisted 9730
- Retrospective Studies 9328
- Magnetic Resonance Imaging 6341
- Reproducibility of Results 5670
- Tomography, X-Ray Computed 4863
- Support Vector Machine 4762
- Computational Biology 4328
- Brain 4125
- Computer Simulation 3932
Recent Journals
- Scientific reports 6689
- Sensors (Basel, Switzerland) 4794
- PloS one 4186
- Neural networks : the official journal of the International Neural Network Society 3026
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1915
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1378
- IEEE journal of biomedical and health informatics 1167
- Journal of chemical information and modeling 1059
- Nature communications 1029
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 872
- Journal of medical Internet research 853
- Briefings in bioinformatics 853