MedTrace Logo

Effectiveness of an Ai-based Endoscopic Ultrasound Navigation System in the Training of Endoscopic Ultrasonics

NCT05421520 · Status: UNKNOWN · Phase: NA · Type: INTERVENTIONAL · Enrollment: 12

Last updated 2023-08-24

No results posted yet for this study

Summary

In the early stage, the investigators successfully constructed an artificial intelligence model-based ultrasonic endoscopy-assisted film reading system and named the modified system biliopancreatic Master. The system can realize real-time ultrasonic station recognition and anatomical mark recognition and provide doctors with corresponding operation techniques. This study aimed to verify the feasibility and effectiveness of the biliopancreatic master system developed by our project team in shortening the training period of ultrasound endoscopists through a single-center clinical study.

Conditions

  • Endoscopic Ultrasound

Interventions

DEVICE

Artificial intelligence assisted 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
HEALTH_SERVICES_RESEARCH
Masking
NONE
Model
PARALLEL

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2023-10-08
Primary Completion
2024-05-31
Completion
2024-05-31

Countries

  • China

Study Locations

More Related Trials

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 NCT05421520 on ClinicalTrials.gov