Non-invasive blood-based detection of endometriosis can improve standard-of-care by facilitating early diagnosis and clinical management among symptomatic women

A minimally invasive, multi-omic blood-based assay integrating molecular biomarkers with machine learning can accurately detect endometriosis across menstrual cycle phases and provides complementary diagnostic values. This approach has the potential to improve early detection, and guide timely clinical intervention. A prospective validation is ongoing in geographically and ethnically diverse populations to further assess its broad clinical utility.