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.
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. .
Study Type
OBSERVATIONAL
Enrollment
150
Fetal weight
Estimation of fetal weight, generated from AI analysis of fetal ultrasound images.
Time frame: 10 minutes
Ultrasound fetal weight estimation
Estimation of fetal weight, calculated from hadlock formula with information from the three standard planes of the head, abdomen and femur.
Time frame: 15 minutes
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