L03 : EndoMetrics: A Multivariable ML-Based Interface for Noninvasive Endometriosis Screening
| Students | Ashley Zhang
Osa Gupta |
| School | HDSB - Iroquois Ridge High School - Oakville |
| Level | Senior 11/12 - Grade 12 |
| Group | Group 12 - Health Science IV |
| Abstract | This project provides a noninvasive, cost-effective endometriosis screening method by leveraging a multivariable predictive machine learning framework. By analyzing clinical data to determine diagnostic likelihood, the platform offers a low-barrier alternative to traditional invasive surgery. This data-driven approach empowers patient advocacy and accelerates specialist intervention, directly addressing the systemic dismissals and normalized symptoms that currently delay women's endometriosis diagnosis by a decade. |