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Colonoscopy

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Colonoscopy with robotic steering and automated lumen centralization: a feasibility study in a colon model.

Endoscopy
BACKGROUND AND STUDY AIMS: We introduced a new platform for performing colonoscopy with robotic steering and automated lumen centralization (RS-ALC) and evaluated its technical feasibility.

Current state of micro-robots/devices as substitutes for screening colonoscopy: assessment based on technology readiness levels.

Surgical endoscopy
BACKGROUND: Previous reports have described several candidates, which have the potential to replace colonoscopy, but to date, there is still no device capable of fully replacing flexible colonoscopy in the management of colonic disorders and for mass...

Polyp Detection via Imbalanced Learning and Discriminative Feature Learning.

IEEE transactions on medical imaging
Recent achievement of the learning-based classification leads to the noticeable performance improvement in automatic polyp detection. Here, building large good datasets is very crucial for learning a reliable detector. However, it is practically chal...

Natural language processing as an alternative to manual reporting of colonoscopy quality metrics.

Gastrointestinal endoscopy
BACKGROUND AND AIMS: The adenoma detection rate (ADR) is a quality metric tied to interval colon cancer occurrence. However, manual extraction of data to calculate and track the ADR in clinical practice is labor-intensive. To overcome this difficulty...

Multi-center colonoscopy quality measurement utilizing natural language processing.

The American journal of gastroenterology
BACKGROUND: An accurate system for tracking of colonoscopy quality and surveillance intervals could improve the effectiveness and cost-effectiveness of colorectal cancer (CRC) screening and surveillance. The purpose of this study was to create and te...

[Role of Artificial Intelligence in Improving Quality of Colonoscopy].

The Korean journal of gastroenterology = Taehan Sohwagi Hakhoe chi
Colorectal cancer is a common malignancy and a major health concern in Korea. Although colonoscopy is an effective tool for screening and preventing colorectal cancer through the early detection of pre-cancerous lesions, many factors influence the qu...

Construction and validation of machine learning-based predictive model for colorectal polyp recurrence one year after endoscopic mucosal resection.

World journal of gastroenterology
BACKGROUND: Colorectal polyps are precancerous diseases of colorectal cancer. Early detection and resection of colorectal polyps can effectively reduce the mortality of colorectal cancer. Endoscopic mucosal resection (EMR) is a common polypectomy pro...

Accurate, Robust, and Scalable Machine Abstraction of Mayo Endoscopic Subscores From Colonoscopy Reports.

Inflammatory bowel diseases
BACKGROUND: The Mayo endoscopic subscore (MES) is an important quantitative measure of disease activity in ulcerative colitis. Colonoscopy reports in routine clinical care usually characterize ulcerative colitis disease activity using free text descr...

The Application Value of an Artificial Intelligence-Driven Intestinal Image Recognition Model to Evaluate Intestinal Preparation before Colonoscopy.

British journal of hospital medicine (London, England : 2005)
Artificial intelligence (AI), with advantages such as automatic feature extraction and high data processing capacity and being unaffected by fatigue, can accurately analyze images obtained from colonoscopy, assess the quality of bowel preparation, a...

Combination of white-light imaging-based and narrow-band imaging-based artificial intelligence models during colonoscopy in patients with ulcerative colitis.

Journal of Crohn's & colitis
BACKGROUND AND AIMS: The long-term treat-to-target (T2T) approach in ulcerative colitis (UC) aims for endoscopic remission, but variability among endoscopists and a lack of precision in relapse prediction both limit its clinical usefulness. A recentl...