NCT06268392

A Comparative Study of AI Methods for Fetal Diagnostic Accuracy in Ultrasound

• Status: Unknown
• Phase: —
• Study type: Observational
• Enrollment: 150 (estimated)
• Sponsor: Copenhagen Academy for Medical Education and Simulation · Academic / Other
• Sex: Female
• Age: 18 Years
• Healthy volunteers: Accepted

Summary

This study serves as a supplemental investigation to the randomized controlled SCAN-AID study (NCT0632187). This study will evaluate and compare the fetal growth estimation outcomes of AI-supported groups, expert sonographers, and control groups using a secondary AI predictive model.

Detailed description

The goal of this study is to compare the effects of two distinct AI methods on fetal ultrasound diagnostic accuracy. It serves as a supplementary investigation to the SCAN-AID study (NCT NCT06232187). This study aims will compare the diagnostic accuracy of two types of AI methods. From the SCAN-AID study ultrasound novices were randomized into one of three groups with different levels of AI support: control group, AI feedback group 1 where the participants are presented with basic black box AI feedback, and AI feedback group 2 where the participants are presented with a more detailed explainable AI feedback. All the participants are tasked to perform an ultrasound fetal weight estimation (EFW) on pregnant women at gestational age 30-37. The outcomes were than compared to the expert sonographers measurements. In this study an operator independent AI method that predicts the fetal weight is used on the SCAN-AID ultrasound examinations. .

Conditions

• Fetal Growth Retardation
• Fetal Macrosomia
• Fetal Growth

Timeline

• Start date: 2024-02-15
• Primary completion: 2024-08-01
• Completion: 2024-08-01
• First posted: 2024-02-20
• Last updated: 2024-02-22