
AI model accurately classifies colorectal polyps
An AI model for automated classification of colorectal polyps could benefit cancer screening programs by improving efficiency, reproducibility, and accuracy.
An AI model for automated classification of colorectal polyps could benefit cancer screening programs by improving efficiency, reproducibility, and accuracy.
A machine learning algorithm helps accurately differentiate benign and premalignant colorectal polyps on CT colonography scans.
Scientists at Purdue University have developed tiny robots that can walk through the colon to deliver drugs precisely where needed.
Scientists have made a breakthrough in their work to develop semi-autonomous colonoscopy, using a robot to guide a medical device into the body.
Researchers have developed a 3D printed ingestable capsule that can capture samples throughout the gut and safely transport these outside the body for testing.
Researchers have used 3D micro-printing to develop the world’s smallest, flexible scope for looking inside blood vessels.
Researchers develop an AI system that effectively evaluates endoscopic mucosal findings from patients with ulcerative colitis without the need for biopsy collection.