An AI model that flags endometriosis risk without surgery, accepted at an IEEE conference

Endometriosis affects about 10% of women of reproductive age, and diagnosis often takes years because it usually requires surgery to confirm. Harleen built EndoRisk-Ensemble, a model that estimates risk from symptoms and clinical history alone. She found that a conventional model scored a high AUC of 0.959 but caught none of the high-risk patients, then fixed it with minority-class oversampling, a three-model ensemble and confidence-weighted voting. Her model reached an AUC of 0.990 and identified 4 of 5 high-risk patients in the held-out test set.