Midwife-Delivered AI Ultrasound to Improve Fetal Growth Monitoring in NHS Maternity Care

This PhD studentship offers the opportunity to conduct a feasibility study testing midwife-led AI ultrasound to improve detection of fetal growth restriction and reduce maternity inequalities in NHS care. Stillbirth affects over 2,800 UK families each year, often linked to undetected fetal growth restriction (FGR). Current screening with tape-measure assessments misses up to 75% of small-for-gestational-age babies, particularly among women with high BMI or from ethnic minority groups. The study will evaluate the feasibility, acceptability, and implementation of midwife-led point-of-care ultrasound (POCUS) powered by artificial intelligence to replace traditional fundal height measurements for fetal growth monitoring in routine NHS antenatal care. The research will take place across NHS hospital trusts where midwives will use a handheld AI-enabled ultrasound device to perform a short, blind abdominal sweep at routine visits. Data will be collected on recruitment, retention, scan quality, usability, and acceptability among women and midwives through qualitative interviews and focus groups. The studentship provides a unique opportunity to contribute to pioneering research integrating AI and midwifery practice to improve early detection of fetal growth issues and address health inequalities in maternal care.