Table 2.

Evaluation of algorithms trained to predict satisfaction with breasts at two-year follow-up.

	2-year follow-up satisfaction lower than baseline		2-year follow-up satisfaction higher than baseline
	Accuracy (95% CI)	AUC (95% CI)	Accuracy (95% CI)	AUC (95% CI)
Logistic regression with elastic net penalty
Test set (n = 1332)	0.84 (0.83–0.85)	0.85 (0.84–0.87)	0.77 (0.76–0.78)	0.85 (0.84–0.86)
Additional validation set (n = 221)	0.83 (0.78–0.88)	0.84 (0.78–0.90)	0.78 (0.72–0.83)	0.87 (0.82–0.91)
XGBoost Tree
Test set (n = 1332)	0.84 (0.82–0.85)	0.85 (0.84–0.87)	0.76 (0.75–0.78)	0.85 (0.83–0.86)
Additional validation set (n = 221)	0.83 (0.77–0.88)	0.84 (0.78–0.90)	0.77 (0.71–0.83)	0.86 (0.81–0.91)
Neural network
Test set (n = 1332)	0.83 (0.82–0.84)	0.86 (0.85–0.87)	0.76 (0.74–0.77)	0.84 (0.83–0.86)
Additional validation set (n = 221)	0.84 (0.78–0.88)	0.85 (0.78–0.90)	0.78 (0.72–0.84)	0.87 (0.83–0.92)

AUC = Area under the Receiver Operating Characteristic Curve.