AIMC Topic: Polyps

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Non-invasive classification of non-neoplastic and neoplastic gallbladder polyps based on clinical imaging and ultrasound radiomics features: An interpretable machine learning model.

European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology Feb 25, 2025
BACKGROUND: Gallbladder (GB) adenomas, precancerous lesions for gallbladder carcinoma (GBC), lack reliable non-invasive tools for preoperative differentiation of neoplastic polyps from cholesterol polyps. This study aimed to evaluate an interpretable...
Male Middle Aged Ultrasonography Aged Adult Radiomics Gallbladder Neoplasms Cholecystectomy Polyps Adenoma Diagnosis, Differential Gallbladder Diseases Humans Machine Learning Retrospective Studies Female
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Establishing a preoperative predictive model for gallbladder adenoma and cholesterol polyps based on machine learning: a multicentre retrospective study.

World journal of surgical oncology Jan 28, 2025
BACKGROUND: With the rising diagnostic rate of gallbladder polypoid lesions (GPLs), differentiating benign cholesterol polyps from gallbladder adenomas with a higher preoperative malignancy risk is crucial. This study aimed to establish a preoperativ...
Machine Learning Prognosis Retrospective Studies Humans Male Middle Aged Ultrasonography Female Aged Adult Gallbladder Neoplasms Polyps Adenoma Diagnosis, Differential Cholesterol ROC Curve Support Vector Machine Follow-Up Studies
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The value of CT radiomics combined with deep transfer learning in predicting the nature of gallbladder polypoid lesions.

Acta radiologica (Stockholm, Sweden : 1987) Apr 16, 2024
BACKGROUND: Computed tomography (CT) radiomics combined with deep transfer learning was used to identify cholesterol and adenomatous gallbladder polyps that have not been well evaluated before surgery.
Adenomatous Polyps Gallbladder Contrast Media Predictive Value of Tests Cholesterol Gallbladder Diseases Gallbladder Neoplasms Polyps Male Humans Middle Aged Deep Learning Machine Learning Adult Retrospective Studies Radiomics Tomography, X-Ray Computed Female Aged
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Assessing generalisability of deep learning-based polyp detection and segmentation methods through a computer vision challenge.

Scientific reports Jan 23, 2024
Polyps are well-known cancer precursors identified by colonoscopy. However, variability in their size, appearance, and location makes the detection of polyps challenging. Moreover, colonoscopy surveillance and removal of polyps are highly operator-de...
Humans Computers Colonoscopy Deep Learning Crowdsourcing Polyps
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Artificial Intelligence in endoscopy: A future poll.

Arab journal of gastroenterology : the official publication of the Pan-Arab Association of Gastroenterology Jan 13, 2024
Artificial Intelligence [AI] has been a trendy topic in recent years, with many developed medical applications. In gastrointestinal endoscopy, AI systems include computer-assisted detection [CADe] for lesion detection as bleedings and polyps and comp...
Artificial Intelligence Endoscopy, Gastrointestinal Polyps Humans
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A deep learning pipeline for automated classification of vocal fold polyps in flexible laryngoscopy.

European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery Sep 11, 2023
PURPOSE: To develop and validate a deep learning model for distinguishing healthy vocal folds (HVF) and vocal fold polyps (VFP) on laryngoscopy videos, while demonstrating the ability of a previously developed informative frame classifier in facilita...
Humans Polyps Deep Learning Neural Networks, Computer Vocal Cords Machine Learning Laryngoscopy Retrospective Studies
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Knowledge, perceptions and behaviours of endoscopists towards the use of artificial intelligence-aided colonoscopy.

Surgical endoscopy Sep 5, 2023
BACKGROUND: Recent developments in artificial intelligence (AI) systems have enabled advancements in endoscopy. Deep learning systems, using convolutional neural networks, have allowed for real-time AI-aided detection of polyps with higher sensitivit...
Polyps Neural Networks, Computer Consultants Artificial Intelligence Humans Colonoscopy
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Analysis of ultrasonographic images using a deep learning-based model as ancillary diagnostic tool for diagnosing gallbladder polyps.

Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver Jul 3, 2023
BACKGROUND: Accurately diagnosing gallbladder polyps (GBPs) is important to avoid misdiagnosis and overtreatment.
Gallbladder Neoplasms Polyps Deep Learning Humans Gastrointestinal Neoplasms Gallbladder Diseases Retrospective Studies
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Polyp segmentation with consistency training and continuous update of pseudo-label.

Scientific reports Aug 26, 2022
Polyp segmentation has accomplished massive triumph over the years in the field of supervised learning. However, obtaining a vast number of labeled datasets is commonly challenging in the medical domain. To solve this problem, we employ semi-supervis...
Image Processing, Computer-Assisted Humans Polyps Supervised Machine Learning Datasets as Topic
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Deep reconstruction-recoding network for unsupervised domain adaptation and multi-center generalization in colonoscopy polyp detection.

Computer methods and programs in biomedicine Dec 5, 2021
BACKGROUND AND OBJECTIVE: Currently, the best performing methods in colonoscopy polyp detection are primarily based on deep neural networks (DNNs), which are usually trained on large amounts of labeled data. However, different hospitals use different...
Colonoscopy Humans Polyps Neural Networks, Computer
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