CT Colonography Identifies Pre-Malignant Polyps with Machine-Based Learning Algorithm
Excerpt from the Article:
Implementing a radiomics-based machine learning algorithm allows CT colonography to differentiate between benign and pre-cancerous polyps with high sensitivity and specificity.
Applying a machine-based learning algorithm to images captured with CT colonography makes it possible for radiologists to differentiate between benign and pre-malignant colorectal polyps.
In industrialized countries across the globe, colorectal cancer ranks among the top three most common causes of cancer-related deaths among both men and women. In a study published Feb. 23 in Radiology, a team of investigators from Germany showed how using radiomics can expand CT colonography beyond simply detecting polyps to pinpointing which ones are likely to progress to being cancerous.
Click the button below to read the entire Article:
Discover What Sets TrialStat Apart From Ordinary EDC Platforms
Click the image or button below to explore our eClinical Suite Platform and discover what sets TrialStat apart from competing EDC platforms.
Request Your Demo Today!
From rapid database build through database lock, we deliver consistent quality on-time and on-budget. Ready to upgrade your eClinical toolkit?