An Artificial Intelligence System for Multimodal, Multi-class Diagnosis of Pancreatic Cystic Lesions Based on Endoscopic Ultrasonography
Qilu Hospital of Shandong University
176 participants
Apr 20, 2026
OBSERVATIONAL
Conditions
Summary
The aim of this study is to develop and validate an artificial intelligence system named iEUS-PCL (intelligent endoscopic ultrasound system-pancreatic cystic lesions） for detecting and multimodal, multi-class diagnosing pancreatic cystic lesions (PCL) during endoscopic ultrasound (EUS) examination.
Eligibility
Plain Language Summary
Simplified for easier understanding
This summary was AI-generated to explain the trial in plain language. It is not medical advice. Always discuss eligibility with your doctor before enrolling in a clinical trial.
Interested in this trial?
Get notified about updates and connect with the research team.
Interventions
The iEUS-PCL will automatically detect pancreatic cystic lesions and integrate the patients' EUS images, EUS features, clinical data and radiological imaging features to perform three classification tasks: 1. binary classification: benign/malignant lesions; 2. binary classification: mucinous/non-mucinous lesions; 3. four-category classification: intraductal papillary mucinous neoplasm/ mucinous cystic neoplasm/ serous cyst neoplasm/ pancreatic cyst.
Locations(1)
View Full Details on ClinicalTrials.gov
For the most up-to-date information, visit the official listing.
NCT07543263