AIMC Topic: Colorectal Neoplasms

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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...

A multi-technique ensemble model leveraging attention mechanism and image processing for enhanced colorectal tumor detection.

Scientific reports
This research introduces an improved method for identifying colorectal tumors through a combination of deep convolutional neural networks (CNNs), transfer learning, and sophisticated image processing techniques used on histopathological images. The s...

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...

Qualitative and quantitative assessment of accelerated liver diffusion-weighted imaging using deep-learning reconstruction in oncologic patients.

BMC medical imaging
BACKGROUND: Deep-learning (DL) reconstructions could improve image quality and reduce acquisition time in diffusion-weighted imaging (DWI). This study assessed, qualitatively and quantitatively, DL-DWI in liver metastasis of colorectal cancer patient...

Automated tumor stroma ratio assessment in colorectal cancer using hybrid deep learning approach.

Scientific reports
The Tumor-Stroma Ratio (TSR) is a critical prognostic factor in colorectal cancer (CRC), offering insights into tumor microenvironment interactions. However, traditional TSR assessment methods are subjective and labor-intensive. This study is among t...

Leveraging Machine Learning and Robotic Process Automation to Identify and Convert Unstructured Colonoscopy Results Into Actionable Data: Proof-of-Concept Study.

JMIR medical informatics
BACKGROUND: With rising patient volumes and a focus on quality, our health system had the objective to create a more efficient way to ensure accurate documentation of colorectal cancer (CRC) screening intervals from inbound colonoscopy reports to ens...

Deep learning with refined single candidate optimizer for early polyp detection.

Scientific reports
Colorectal cancer (CRC) is one of the most common sources of cancer-related death worldwide. Early detection of these precancerous polyps with the aid of colonoscopy plays an important role in decreasing the burden of CRC. By employing novel optimiza...

AI-driven pre-screening for colorectal cancer using complete blood counts: toward broader population impact.

International journal of colorectal disease
PURPOSE: Early colorectal cancer (CRC) detection is crucial for effective treatment; however, traditional screening methods face challenges. Colonoscopy, though highly effective, has limited availability, and fecal immunochemical tests (FIT) are more...