Modeling cycle phases using hormone trajectories in women with and without polyendocrine metabolic ovarian syndrome
This study utilizes self-tracked urinary hormone data to develop an autoregressive Hidden Markov model that accurately maps menstrual cycle phases, revealing distinct hormonal differences in women with polyendocrine metabolic ovarian syndrome (PMOS) and demonstrating the model's potential for non-invasive PMOS screening and improved clinical testing protocols.