AIMC Topic: Adenoma

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Improving Colorectal Cancer Detection with AI-Assisted Colonoscopy: A Systematic Review and Meta-Analysis of 38 RCTs with GRADE Assessment.

Journal of gastrointestinal cancer
BACKGROUND: Colorectal cancer (CRC) remains a leading cause of cancer-related mortality worldwide. Early detection of precancerous lesions such as adenomas and polyps is vital for prevention, yet standard colonoscopy may miss up to 26% of adenomas. A...

Clinical Efficacy of Real-Time Artificial Intelligence-Assisted Colonoscopy in Colorectal Polyp Detection: A Prospective Multicenter Randomized Controlled Trial.

Gut and liver
BACKGROUND/AIMS: Early detection and removal of colon polyps are critical for preventing colorectal cancer. Computer-aided detection (CADe) systems have been introduced to increase the polyp detection rate (PDR) during colonoscopy, potentially enhanc...

Structured Integration of an Artificial Intelligence-Based System for the Optical Diagnosis of Colorectal Polyps.

Gut and liver
BACKGROUND/AIMS: Recent advances in computer-aided diagnosis (CADx) systems have demonstrated expert-level accuracy in the optical diagnosis of colorectal polyps. High-confidence (HC) diagnoses have been defined as those made within 3 seconds without...

Colonoscopy Quality and Strategies for Improvement.

Gut and liver
Colonoscopy plays a pivotal role in colorectal cancer (CRC) screening and reduces CRC incidence and mortality. Its effectiveness depends on colonoscopist performance, which can vary. Missed lesions during colonoscopy can lead to post-colonoscopy CRC ...

Effectiveness of artificial intelligence-assisted colonoscopy in detecting and diagnosing colorectal tumors: a systematic review and network meta-analysis.

International journal of colorectal disease
BACKGROUND: The emergence of artificial intelligence (AI) has greatly promoted the development of the field of medical image analysis, but the potential benefits of AI-assisted colonoscopy and diagnosis (CADe/CADx) for the detection rate of colorecta...

Development of deep learning-based narrow-band imaging endocytoscopic classification for predicting colorectal lesions from a retrospective study.

Nature communications
Data-driven approaches have advanced colorectal lesion diagnosis in digestive endoscopy, yet their application in endocytoscopy (EC)-a high-magnification imaging technique-remains limited, with most studies relying on conventional machine learning me...

Plasma Proteomic High-Performance Biomarkers for Early Diagnosis of Colorectal Cancer.

Journal of proteome research
Colorectal cancer (CRC) is a major global health challenge due to its high incidence, mortality, and low rate of early detection. Early diagnosis, targeting precancerous lesions (advanced adenomas) and early stage CRC (Tis and T1), is critical for im...

Artificial intelligence-based CT histogram parameters differentiating bronchiolar adenoma and lung adenocarcinomas: A two-center study.

PloS one
PURPOSE: Bronchiolar adenoma (BA) is a rare benign pulmonary neoplasm originating from the bronchial mucosal epithelium and mimics lung adenocarcinoma (LAC) both radiographically and microscopically. This study aimed to develop a nomogram for disting...

Colonoscopy in obese patients: challenges and emerging solutions.

Current opinion in gastroenterology
PURPOSE OF REVIEW: The rising prevalence of obesity, now affecting over 40% of U.S. adults, poses critical implications for colorectal cancer screening, as obesity increases the risk of both colorectal adenomas and cancer. Despite these elevated risk...