14 citations · 50 across the 10 of their papers we have counts for
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cs.LG2021★ 6 cited
A generative, predictive model for menstrual cycle lengths that accounts for potential self-tracking artifacts in mobile health data
Kathy Li, Iñigo Urteaga, Amanda Shea +3
Mobile health (mHealth) apps such as menstrual trackers provide a rich source of self-tracked health observations that can be leveraged for health-relevant research. However, such…
cs.LG2019★ 3 cited
Multi-Task Gaussian Processes and Dilated Convolutional Networks for Reconstruction of Reproductive Hormonal Dynamics
Iñigo Urteaga, Tristan Bertin, Theresa M. Hardy +2
We present an end-to-end statistical framework for personalized, accurate, and minimally invasive modeling of female reproductive hormonal patterns. Reconstructing and forecasting…