AIMC Topic: Colonoscopy

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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...

Ulcerative Colitis Severity Classification and Localized Extent (UC-SCALE): An Artificial Intelligence Scoring System for a Spatial Assessment of Disease Severity in Ulcerative Colitis.

Journal of Crohn's & colitis
BACKGROUND AND AIMS: Validated scoring methods such as the Mayo Clinic Endoscopic Subscore (MCES) evaluate ulcerative colitis (UC) severity at the worst colon segment, without considering disease extent. We present the Ulcerative Colitis Severity Cla...

Artificial Intelligence-assisted Video Colonoscopy for Disease Monitoring of Ulcerative Colitis: A Prospective Study.

Journal of Crohn's & colitis
BACKGROUNDS AND AIMS: The Mayo endoscopic subscore [MES] is the most popular endoscopic disease activity measure of ulcerative colitis [UC]. Artificial intelligence [AI]-assisted colonoscopy is expected to reduce diagnostic variability among endoscop...

[Effect of an artificial intelligence-assisted recognition system on colonoscopy quality].

Zhonghua nei ke za zhi
To explore the value of the artificial intelligence (AI)-assisted recognition system in the detection quality of colonoscopy. From January 2023, the data on 700 patients who underwent colonoscopy in the Digestive Endoscopy Center of the First Affil...

Hyperspectral imaging facilitating resect-and-discard strategy through artificial intelligence-assisted diagnosis of colorectal polyps: A pilot study.

Cancer medicine
BACKGROUND AND AIMS: The resect-and-discard strategy for colorectal polyps based on accurate optical diagnosis remains challenges. Our aim was to investigate the feasibility of hyperspectral imaging (HSI) for identifying colorectal polyp properties a...

Effect of artificial intelligence implementation to the latest generation 4K colonoscopy.

Polski przeglad chirurgiczny
<b>Indroduction:</b> Colonoscopy is an acclaimed screening test to detect colorectal cancer (CRC). The most important quality indicators for colonoscopy are adenoma detection rate (ADR), cecal intubation rate (CIR), withdrawal time (WT), ...

Integrating artificial intelligence techniques for advancements in colorectal cancer management: navigating past and predicting future direction.

JPMA. The Journal of the Pakistan Medical Association
Artificial Intelligence (AI) in the last few years has emerged as a valuable tool in managing colorectal cancer, revolutionizing its management at different stages. In early detection and diagnosis, AI leverages its prowess in imaging analysis, scrut...

Improving the Computer-Aided Estimation of Ulcerative Colitis Severity According to Mayo Endoscopic Score by Using Regression-Based Deep Learning.

Inflammatory bowel diseases
BACKGROUND: Assessment of endoscopic activity in ulcerative colitis (UC) is important for treatment decisions and monitoring disease progress. However, substantial inter- and intraobserver variability in grading impairs the assessment. Our aim was to...