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Effect of a Deep Learning-based Bile Duct Scanning System on the Diagnostic Accuracy of Common Bile Duct Stones During Examination by Novice Ultrasound Endoscopists

NCT05381064 · Status: UNKNOWN · Phase: NA · Type: INTERVENTIONAL · Enrollment: 184

Last updated 2022-05-19

No results posted yet for this study

Summary

The bile duct scanning system based on deep learning can prompt endoscopists to scan standard stations and identify bile ducts and stones in real time. The purpose of this study is to evaluate the effectiveness and safety of the proposed deep learning-based bile duct scanning system in improving the diagnostic accuracy of common bile duct stones and reducing the rate of missed gallstones during bile duct scanning by novice ultrasound endoscopists in a single-center, tandem, randomized controlled trial

Conditions

  • Common Bile Duct Stones

Interventions

DEVICE

artificial intelligence assistance system

A deep learning-based bile duct scanning system that can prompt endoscopists to scan standard stations, identify bile ducts and stones in real time

Sponsors & Collaborators

  • Renmin Hospital of Wuhan University

    lead OTHER

Principal Investigators

  • Yu Honggang, Doctor · Renmin Hospital of Wuhan University

Study Design

Allocation
RANDOMIZED
Purpose
DIAGNOSTIC
Masking
DOUBLE
Model
CROSSOVER

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2022-06-01
Primary Completion
2023-12-01
Completion
2024-01-01

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT05381064 on ClinicalTrials.gov