J03 : A Novel Machine Learning Model for Noninvasive Diagnosis of Endometriosis


Students Gabriella Ipwanshek
School HDSB - White Oaks Secondary School - Oakville
Level Intermediate 9/10 - Grade 10
Group Group 8 - Engineering and Computing II
Abstract Endometriosis is an extremely prevalent condition, affecting one in ten women of childbearing age worldwide. Currently endometriosis diagnosis relies heavily on invasive methods for a definitive diagnosis. This project aims to leverage machine learning to develop a noninvasive AI model for diagnosing endometriosis. By analyzing clinical features and symptoms, this model aims to provide a faster, more accessible, and cost-effective alternative to traditional diagnostic procedures.
Awards
Group Award Prize
Merit AwardsBronze Merit Award$ 60