AIMC Topic: Adenoma
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Impact of study design on adenoma detection in the evaluation of artificial intelligence-aided colonoscopy: a systematic review and meta-analysis.
Gastrointestinal endoscopy
Jan 24, 2024
BACKGROUND AND AIMS: Randomized controlled trials (RCTs) have reported that artificial intelligence (AI) improves endoscopic polyp detection. Different methodologies-namely, parallel and tandem designs-have been used to evaluate the efficacy of AI-as...
Use of a Novel Artificial Intelligence System Leads to the Detection of Significantly Higher Number of Adenomas During Screening and Surveillance Colonoscopy: Results From a Large, Prospective, US Multicenter, Randomized Clinical Trial.
The American journal of gastroenterology
Jan 18, 2024
INTRODUCTION: Adenoma per colonoscopy (APC) has recently been proposed as a quality measure for colonoscopy. We evaluated the impact of a novel artificial intelligence (AI) system, compared with standard high-definition colonoscopy, for APC measureme...
Linked-color imaging with or without artificial intelligence for adenoma detection: a randomized trial.
Endoscopy
Jan 8, 2024
BACKGROUND: Adenoma detection rate (ADR) is an important indicator of colonoscopy quality and colorectal cancer incidence. Both linked-color imaging (LCI) with artificial intelligence (LCA) and LCI alone increase adenoma detection during colonoscopy,...
Current status of artificial intelligence technologies in pituitary adenoma surgery: a scoping review.
Pituitary
Jan 6, 2024
PURPOSE: Pituitary adenoma surgery is a complex procedure due to critical adjacent neurovascular structures, variations in size and extensions of the lesions, and potential hormonal imbalances. The integration of artificial intelligence (AI) and mach...
Efficacy of artificial intelligence in reducing miss rates of GI adenomas, polyps, and sessile serrated lesions: a meta-analysis of randomized controlled trials.
Gastrointestinal endoscopy
Jan 4, 2024
BACKGROUND AND AIMS: The aim of this study was to determine if utilization of artificial intelligence (AI) in the course of endoscopic procedures can significantly diminish both the adenoma miss rate (AMR) and the polyp miss rate (PMR) compared with ...
Endorobotic submucosal dissection of rectal lesions using the single port robot DaVinci-SP: initial experience of the first 10 cases.
ANZ journal of surgery
Nov 27, 2023
BACKGROUND: Endoluminal surgery is increasingly recognized as a mode of treatment for colorectal neoplasms with the latest robotic single port platform Da Vinci-SP (Intuitive Surgical, Sunnyvale) facilitating submucosal dissection of benign rectal ne...
Deep learning based identification of pituitary adenoma on surgical endoscopic images: a pilot study.
Neurosurgical review
Nov 1, 2023
Accurate tumor identification during surgical excision is necessary for neurosurgeons to determine the extent of resection without damaging the surrounding tissues. No conventional technologies have achieved reliable performance for pituitary adenoma...
Deep Learning-Based Differential Diagnosis of Follicular Thyroid Tumors Using Histopathological Images.
Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Jul 31, 2023
Deep learning systems (DLSs) have been developed for the histopathological assessment of various types of tumors, but none are suitable for differential diagnosis between follicular thyroid carcinoma (FTC) and follicular adenoma (FA). Furthermore, wh...
Deep learning approach for differentiating indeterminate adrenal masses using CT imaging.
Abdominal radiology (New York)
Jun 27, 2023
PURPOSE: Distinguishing stage 1-2 adrenocortical carcinoma (ACC) and large, lipid poor adrenal adenoma (LPAA) via imaging is challenging due to overlapping imaging characteristics. This study investigated the ability of deep learning to distinguish A...
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