Greensburg

This research aims to evaluate the clinical validity of a deep neural network algorithm called EndoCheck, which detects protein biomarkers to help diagnose endometriosis in women experiencing chronic pelvic pain. The study compares EndoCheck's performance against laparoscopic surgical assessment, focusing on its sensitivity and specificity as a diagnostic tool. The goal is to confirm the test meets success criteria of at least 94% sensitivity and 79% specificity, and to examine its accuracy across different levels of pain severity and other clinical factors. The study is observational and does not involve any intervention or treatment. Women scheduled for laparotomy or laparoscopy due to symptoms suggestive of endometriosis will be assessed using EndoCheck. The study includes female participants aged 14 to 50 years. There are no medications or devices administered as part of the study beyond the use of EndoCheck for biomarker detection. Participants will be involved for a total of 24 months, during which researchers will measure the sensitivity and specificity of the EndoCheck test compared to surgical findings. The study includes informed consent, clinical evaluations, and monitoring of test performance. Safety and health status are monitored to ensure participant well-being, and outcome measures focus on diagnostic accuracy to support EndoCheck's use as an aid in diagnosing endometriosis.