An AI-powered app is being developed by a Toronto Metropolitan University professor that will help doctors detect endometriosis earlier and reduce delays patients may face before receiving a diagnosis.
The professor’s team uses MRI data, patient records and clinical notes to identify patterns that may be missed during diagnosis. They are applying this approach to pelvic health research through DANA – short for Diagnostic AI for Navigating Abdominopelvic Pain. Unlike basic symptom-tracking apps, DANA is designed to feel like a guided conversation with an expert clinician, asking smart follow-up questions in the right sequence.
The app will analyze how patients describe their symptoms, combine that information with individual health details, and generate tailored recommendations. By analyzing patterns within symptoms, clinical narratives, and imaging reports, DANA equips doctors with comprehensive information, enabling patients to receive answers more quickly.
This work aims to more quickly connect patients with the appropriate specialist, assist doctors in identifying likely causes of chronic pelvic pain, minimize unnecessary procedures and make diagnosis more equitable for all Canadians.
For more information, visit Toronto Metropolitan University
