Hybrid risk scores integrating polygenic and clinical variables for endometriosis prediction

BackgroundEndometriosis affects approximately 10% of reproductive-age women and is associated with substantial diagnostic delay and heterogeneous symptom presentation. Prior machine-learning prediction models have relied on comorbidity data alone or on small candidatevariant genetic scores, with inc