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: * Which type of artificial intelligence support system works for novices in improving the ultrasound fetal weight diagnostic accuracy? * Does the artificial intelligence improve image quality, evaluate the cognitive load placed on participants when utilizing AI support, and is the AI system usable for novices? 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.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
DIAGNOSTIC
Masking
SINGLE
Enrollment
75
AI feedback in two levels, in aid of the participants, to obtain the right standardplane images used in fetal ultrasound EFW calculation.
Rigshospitalet
Copenhagen, Denmark
Diagnostic accuracy
The accuracy in each group was defined as the percentage difference between estimated fetal weight and the sonographer expert EFW
Time frame: 15 minutes
Image Quality
Salomon criteria score is used to rate the image quality. Points are given depending on the number of landmarks present, quality of the image optimization and caliper.placements. Minimum: 1 Maximum: 18. A higher score indicates a better image quality.
Time frame: 5 minutes pr. participant
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