Artificial Intelligence in Endoscopic Ultrasound to Detect Pancreatic Abnormalities

What this Trial Is About

Researchers are evaluating an artificial intelligence (AI) system designed to detect pancreatic abnormalities identified during endoscopic ultrasound (EUS) procedures. The study focuses on whether this AI can match the findings of trained endoscopists who use EUS, a technique that provides detailed images of organs like the pancreas and liver. This research aims to potentially reduce human error and the learning curve involved in interpreting these ultrasound images for diagnosing pancreatic diseases. Participants will undergo their planned endoscopic ultrasound procedures as usual. During the examination, any abnormalities in the pancreas found by the endoscopist will be compared to those detected by the AI platform. The study involves observing and correlating the AI's detection capabilities with the endoscopist's findings without altering the clinical procedure. Participants will be involved during their scheduled EUS examination, where the AI system will analyze the ultrasound images in real time or afterward. The main outcome measured is the rate at which the AI detects pancreatic abnormalities on the day of the procedure. Additional outcomes include the detection rates of pancreatic solid masses and cystic lesions. The study will monitor these detection rates to assess the AI's performance and potential clinical value.

Artificial Intelligence in Endoscopic Ultrasound