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

Endometriosis Clinical Trial

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

Clinical Trial 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

Clinical Trial 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. ;

Study Design

Related Conditions & MeSH terms

Clinical Trial Details
NCT number NCT05245695
Study type Observational
Source Aspira Women's Health
Contact Silvana Franco
Phone 844-277-4721
Email sfranco@aspirawh.com
Status Recruiting
Phase
Start date July 12, 2022
Completion date July 31, 2024
View Details
See also
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