A Comparative Study of AI Methods for Fetal Diagnostic Accuracy in Ultrasound
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.
- EligibilityCriteria: Pregnant women:  Inclusion Criteria:  Singelton pregnant. Gestational age: 30-38 weeks Maternal age < 40 years  Exclusion Criteria:  Oligo hydramnion Severe fetal anomaly e.g. fetal heart anomaly, omphalocele etc. Severe fetal macrosomia or growth restriction. - HealthyVolunteers: Accepts Healthy Volunteers - Gender: Female - MinimumAge: 18 Years - StdAgeList: Adult, Older Adult - StudyPopulation: Medical students are recruited from the Medical universities in Denmark (mainly Copenhagen University) Pregnant women are chosen from the fetal medical departement at Rigshospitalet, Copenhagen. - SamplingMethod: Non-Probability Sample