Evaluating the added value of salivary hormones in the context of menstrual cycle staging: A machine learning approach and app-implementation.

Journal: Psychoneuroendocrinology
Published Date:

Abstract

OBJECTIVE: Salivary hormone assessment is commonly used in menstrual cycle studies, but its validity for accurate menstrual cycle staging has been questioned. In the present study, we explore possibilities and limitations of salivary hormone assessment for menstrual cycle staging using a machine-learning approach. Specifically, we determine, how saliva sampling should be scheduled in various scenarios to maximize prediction accuracy of menstrual cycle phases from salivary estradiol and progesterone.

Authors

  • Alexander Rietzler
    Department of Psychology & Centre for Cognitive Neuroscience, University of Salzburg, Salzburg, Austria.
  • Tobias Hausinger
    Department of Psychology & Centre for Cognitive Neuroscience, University of Salzburg, Salzburg, Austria.
  • Belinda Pletzer
    Department of Psychology & Centre for Cognitive Neuroscience, University of Salzburg, Salzburg, Austria. Electronic address: Belinda.Pletzer@plus.ac.at.