This article reveals the complexities of risk stratification in fetal growth restriction, highlighting the roles of Doppler ultrasound and artificial intelligence in improving outcomes.
Risk stratification is a core challenge in fetal growth restriction (FGR) care, in part because FGR does not represent a single diagnosis but instead is a finding that is associated with morbidity. Considerable effort has been invested in the development and study of methods to identify fetuses at risk of morbidity and who warrant intervention across multiple domains: Doppler ultrasound, maternal biomarkers, multivariable modeling, and artificial intelligence. It is likely that the most promising advances will integrate findings from across these domains, but further investigation remains necessary.
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Post et al. (2025) studied this question.
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