Aris Papageorghiou MBChB MD FRCOG FAIUM (Hon)
University of Oxford

Artificial intelligence (AI) is transforming ultrasound imaging in obstetrics by enhancing pattern recognition, supporting basic ultrasound acquisition, improving screening, and enabling new approaches to biomarker discovery. In this presentation I will present recent advances that demonstrate that AI can achieve performance comparable to expert clinicians in tasks such as peer review of image quality, detection of breech presentation, congenital anomalies, and gestational age estimation directly from ultrasound images. Such automated techniques offer opportunities to address key challenges in our field, including operator variability and the need for consistent high-quality imaging - with particular promise for underserved regions. I will also discuss that, while AI supports workflow efficiency and diagnostic accuracy, its integration requires careful attention to explainability, trust, and validation in real-world settings. Ongoing developments in machine learning, including unsupervised approaches, generative models and digital twins point to a future where our practice of fetal ultrasound will be significantly augmented by data-driven technologies.