Artificial Intelligent Accelerates the Learning Curve for Mastering Contrast-enhanced Ultrasound of Thyroid Nodules
Artificial Intelligent Accelerates the Learning Curve for Mastering Thyroid Imaging Reporting and Data System of Contrast-enhanced Ultrasound
Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
1,000 participants
Jan 3, 2024
OBSERVATIONAL
Conditions
Summary
The goal of this observational study is to learn about the learning curve for mastering the thyroid imaging reporting and data system of contrast-enhanced ultrasound with the assistance of artificial intelligence in patients with thyroid nodules. The main questions it aims to answer are: 1. Can we develop a artificial intelligent software to assist doctors in the diagnosis of thyroid nodules using contrast-enhanced ultrasound? 2. Can artificial intelligent reduce the number of cases and time for doctors to master the contrast-enhanced ultrasound diagnosis of thyroid nodules? Participants will be asked to undergo contrast-enhanced ultrasound examination and ultrasound-guided fine-needle aspiration of thyroid nodules. Researchers will compare the number of cases and time for doctors with and without artificial intelligent assistance to master the contrast-enhanced ultrasound diagnosis of thyroid nodules to see if artificial intelligent reduce the number of cases and time.
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
Artificial intelligence assisted radiologists to extract ultrasound features of thyroid nodules.
Locations(1)
View Full Details on ClinicalTrials.gov
For the most up-to-date information, visit the official listing.
NCT05982821