6 citations · 6 across the 1 of their papers we have counts for
2 papers
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…
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…