Performance of machine learning algorithms for hysterectomy risk prediction among women with endometriosis in the United States.

Challenge

Hysterectomy risk prediction in endometriosis patients could enable more personalized clinical management, but the performance of machine learning algorithms for this prediction task in a large real-world endometriosis cohort had not been evaluated.

Solution

Target RWE researchers evaluated the performance of multiple machine learning algorithms for hysterectomy risk prediction among women with endometriosis using real-world clinical data, comparing ML approaches against traditional logistic regression.