Ignite Creation Date:
2024-05-06 @ 8:14 PM
Last Modification Date:
2024-10-26 @ 3:23 PM
Study NCT ID:
NCT06306599
Status:
COMPLETED
Last Update Posted:
2024-03-12
First Post:
2024-02-23
Brief Title:
Ultrasound Operator Influence on Diagnostics With AI for Thyroid Nodules - Clinial Trial
Sponsor:
Rigshospitalet Denmark
Organization:
Rigshospitalet Denmark
Study Overview
Official Title:
The Ultrasound Operators Influence on the Diagnostic Accuracy of Artificial Intelligence for Thyroid Nodules Assessment - a Clinical Trial
Status:
COMPLETED
Status Verified Date:
2024-03
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
Brief Summary:
This is a prospective clinical study aiming to test how the experience of the ultrasound operator influences the performance of AI-based artificial intelligence-based diagnostics when analysing thyroid nodules on ultrasound scans The investigators set up an experiment with five stations each with a patient with a thyroid nodule and an ultrasound machine with the deep learning based system S-Detect for Thyroid installed 20 study participants where recruited 8 medical students of novice ultrasound skill 3 junior ENT ear-nose-throat registrars of intermediate ultrasound skill and 9 senior ENT registrars experienced in ultrasound The participants scanned all the patients and recorded their analyses of the nodules using the EUTIRADS European thyroid imagining reporting and data system system in three different ways a analysis of their own S-Detects analysis and an analysis combining the two previous
The hypothesis was that the AI system would perform equally well when between the participant groups In addition it was expected that the experienced participants would perform better than the students without AI help and that the doctors would gain little from AI input but that the students would have their performance improved by AI input
The hypothesis was that the AI system would perform equally well when between the participant groups In addition it was expected that the experienced participants would perform better than the students without AI help and that the doctors would gain little from AI input but that the students would have their performance improved by AI input
Detailed Description:
None
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None