NCT05245695

Deep Neural Network Stratification for Use Detecting Endometriosis in Women Affected by Chronic Pelvic Pain (EndoCheck)

Deep Neural Network Stratification for the Use in Detecting Endometriosis in Women Affected by Chronic Pelvic Pain (EndoCheck)

• Status: Recruiting
• Phase: —
• Study type: Observational
• Enrollment: 1,200 (estimated)
• Sponsor: Aspira Women's Health · Industry
• Sex: Female
• Age: 14 Years – 50 Years
• Healthy volunteers: Not accepted

Summary

The goal of this observational study is to determine the clinical validity of a deep neural network algorithm that utilizes protein biomarker detection of Endometriosis - "EndoCheck" - as an "aid in diagnosis" for endometriosis and to show validity as a diagnostic test

Detailed description

The objective is to confirm the clinical performance (sensitivity and specificity) of EndoCheck when compared to laparoscopic surgical assessment as an "aid in diagnosis" for endometriosis in subjects who present with chronic pelvic pain. The primary endpoint of the study is to optimize the test to achieve the success criteria of at least 94% and 79% sensitivity and specificity, respectively. Secondary endpoints include examining the performance of the test in patients stratified by pain severity and other clinical factors.

Conditions

• Endometriosis

Interventions

Type	Name	Description
OTHER	Observational study, no intervention	Observational study, no intervention

Timeline

• Start date: 2022-07-12
• Primary completion: 2026-06-30
• Completion: 2026-06-30
• First posted: 2022-02-18
• Last updated: 2025-06-25

Locations

10 sites across 1 country: United States