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Impact of AI Feedback on Ultrasound Biometry Accuracy Across the Expertise Levels

NCT07476638 · Status: NOT_YET_RECRUITING · Phase: NA · Type: INTERVENTIONAL · Enrollment: 75

Last updated 2026-03-31

No results posted yet for this study

Summary

Objective: To evaluate the impact of real-time AI feedback on fetal biometry accuracy and investigate the Expertise Reversal Effect-whether AI benefits diminish as user experience increases.

Design: A stratified randomized trial of 75 participants (25 Novices, 25 Intermediates, 25 Experts). Users are randomized 1:1 to either AI-assisted or manual measurement groups.

Outcomes:

* Primary: EFW accuracy (MAPE) compared to actual birthweight.
* Secondary: Procedure time, image quality, error relative to baseline scans, and cognitive workload (NASA-TLX).

Conditions

  • Fetal Growth Abnormalities
  • Fetal Weight

Interventions

DEVICE

AI interventional group

Participants in the intervention arm perform fetal biometry with the assistance of real-time Artificial Intelligence (AI) feedback software.

Sponsors & Collaborators

  • Rigshospitalet, Denmark

    collaborator OTHER

  • Slagelse Hospital

    collaborator OTHER

  • Copenhagen Academy for Medical Education and Simulation

    lead OTHER

Study Design

Allocation
RANDOMIZED
Purpose
DIAGNOSTIC
Masking
SINGLE
Model
PARALLEL

Eligibility

Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2026-03-01
Primary Completion
2027-03-01
Completion
2027-03-01

Countries

  • Denmark

Study Locations

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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 NCT07476638 on ClinicalTrials.gov