Wearable Sensors Reveal Menses-Driven Changes in Physiology and Enable Prediction of the Fertile Window: Observational Study.

Brianna Mae Goodale Mohaned Shilaih Lisa Falco Franziska Dammeier Györgyi Hamvas Brigitte Leeners

Published in: Journal of medical Internet research (2019)

Our contributions highlight the impact of artificial intelligence and machine learning's integration into health care. By monitoring numerous physiological parameters simultaneously, wearable technology uniquely improves upon retrospective methods for fertility awareness and enables the first real-time predictive model of ovulation.

Keyphrases

artificial intelligence
machine learning
healthcare
big data
heart rate
deep learning
polycystic ovary syndrome
cross sectional
genome wide
single cell
low cost
blood pressure
adipose tissue
metabolic syndrome
gene expression
type diabetes