Pregnancy

Benefit of the N-of-1 Approach Versus Aggregate Analysis in Tracking Individual Trajectories During Pregnancy: Comparison of Longitudinal Wearable Observational Studies
Comparing aggregate and individual-level (N-of-1) analyses of Oura Ring and smartphone survey data from 256 pregnant participants in the BUMP study shows that population-level trends often fail to reflect individual pregnancy trajectories, supporting personalized wearable-based monitoring.
Tina Behrouzi, Jennifer Yu, Robin Yang, Adrien Boch, Anna Goldenberg, Sarah M. Goodday, Stephen H. Friend
Cite DOI Full text (PubMed Central) medRxiv preprint
Towards a personalized pregnancy experience: Forecasting symptoms using graph neural networks and digital health technologies
A graph neural network that forecasts third-trimester pregnancy symptoms (edema and fatigue) from wearable physiological data and daily app surveys, with heart rate variability and low-intensity activity emerging as key predictors.
Rui Zhu, Jennifer Yu, Stephen H. Friend, Sarah M. Goodday, Bo Wang, Anna Goldenberg
PDF Cite Code PMLR