4 citations · 4 across the 1 of their papers we have counts for
2 papers
q-bio.QM2019
Characterizing physiological and symptomatic variation in menstrual cycles using self-tracked mobile health data
Kathy Li, Iñigo Urteaga, Chris H. Wiggins +4
The menstrual cycle is a key indicator of overall health for women of reproductive age. Previously, menstruation was primarily studied through survey results; however, as menstrual…
stat.ML2017★ 4 cited
Towards Personalized Modeling of the Female Hormonal Cycle: Experiments with Mechanistic Models and Gaussian Processes
Iñigo Urteaga, David J. Albers, Marija Vlajic Wheeler +3
In this paper, we introduce a novel task for machine learning in healthcare, namely personalized modeling of the female hormonal cycle. The motivation for this work is to model the…