AI and Reproductive Biomarkers: From Hormones to Imaging and Omics

Reproductive health is shaped by biomarkers spanning hormones, ultrasound, genetics, metabolic markers, and longitudinal clinical history. Advances in wearables, at-home diagnostics, and mobile health platforms now enable more continuous and real-world data collection at scale. Combined with AI, these data streams can improve characterization of fertility, pregnancy, gynecologic disease, menopause, and long-term health risk, enabling earlier detection, more personalized treatment, and better outcome prediction.

Our workshop brings together perspectives from machine learning, reproductive medicine, and biomedical science to advance AI for reproductive biomarkers and women’s health. 

Workshop runs 9.30am-2.30pm with networking lunch and refreshments included. 

Places are limited, so early sign up is recommended.

This workshop is organised by the ai@cam-funded Womb to World project in collaboration with Cambridge Reproduction.

Workshop organisers: Dr Staci Weiss (Computer Science & Technology), May Levin (Computer Science & Technology), Moe Vali (Physics), Christina Rozeik (Cambridge Reproduction).