Scan-AId: Artificial Intelligence Support in Novice's Decision-making for Assessing Ultrasound Fetal Weight Estimation - A Randomized Trial
Scan-AId: Artificial Intelligence Support in Novice's Decision-making for Assessing Ultrasound Fetal Weight Estimation - A Randomized Trial
The SCAN-AID study is a prospective, randomized, controlled, and unblinded study that compares the performance of novices in ultrasound fetal weight estimation. The study evaluates the impact of two levels of AI support: a straightforward black box AI and a more detailed explainable AI.
The goal of this randomized controlled clinical trial is to learn which type of artificial intelligence (AI) effects the diagnostic accuracy of ultrasound estimation of fetal weight (EFW), when performed by novices, in this study represented by medical students.
The study's objectives are:
Participants will be tasked with conducting an ultrasound Estimated Fetal Weight (EFW) using either a simple black box AI or a detailed explainable AI feedback system. The AI systems will assist participants in determining if they have captured the appropriate image for EFW. The outcomes will then be compared to those of a control group.
Ultrasound procedures will be performed on pregnant women with fetuses at a gestational age of 28-42 weeks, who have previously undergone an EFW by an expert sonographer or doctor at the clinic within 5 days days leading up to the examinationday. One participant of each randomization arm, will perfrom an EFW on the same pregnant woman.
Ultrasound novice participants:
Inclusion Criteria:
Exclusion Criteria:
• Medical students who received formal fetal or abdominal training prior to the inclusion in this study.
Pregnant women;
Inclusion Criteria:
Exclusion Criteria: