Table 3.

Comparison of ML model accuracy to diagnose endometriosis.

Datasets	Random Forest			XGBoost			AdaBoost			Logistic regression
	AUC	Sensitivity	Specificity	AUC	Sensitivity	Specificity	AUC	Sensitivity	Specificity	AUC	Sensitivity	Specificity
1	0.935	0.871	1	0.952	0.903	1	0.935	0.871	1	0.887	0.774	1
2	0.984	0.968	1	0.984	0.968	1	0.984	0.968	1	0.968	0.935	1
3	0.984	0.968	1	0.952	0.903	1	0.984	0.968	1	0.984	0.968	1
4	0.912	0.935	0.889	0.896	0.903	0.889	0.912	0.935	0.889	0.919	0.839	1
5	0.967	0.933	1	0.967	0.933	1	0.9	0.9	0.9	0.933	0.867	1
6	0.896	0.903	0.889	0.896	0.903	0.889	0.88	0.871	0.889	0.912	0.935	0.889
7	0.984	0.968	1	0.984	0.968	1	0.984	0.968	1	0.984	0.968	1
8	0.952	0.903	1	0.968	0.935	1	0.935	0.871	1	0.919	0.839	1
9	0.968	0.935	1	0.968	0.935	1	0.935	0.871	1	0.864	0.839	0.889
10	0.983	0.967	1	0.967	0.933	1	0.95	0.9	1	0.883	0.767	1