TABLE 1.

Accuracy, sensitivity, and specificity of each machine learning model.

Model types	Cohorts	Accuracy (95% CI)	Sensitivity	Specificity
KNN	Training cohort	0.76 (0.60–0.88)	0.80	0.72
	Internal validation	0.67 (0.51–0.87)	0.80	0.50
	External validation	0.73 (0.56–0.86)	0.75	0.70
NB	Training cohort	0.64 (0.50–0.78)	0.95	0.36
	Internal validation	0.56 (0.41–0.78)	1.00	0.00
	External validation	0.55 (0.40–0.70)	1.00	0.10
SVM	Training cohort	0.89 (0.74–0.96)	0.85	0.91
	Internal validation	0.68 (0.42–0.87)	0.80	0.51
	External validation	0.75 (0.59–0.87)	0.75	0.75
RF	Training cohort	0.83 (0.69–0.93)	0.95	0.73
	Internal validation	0.72 (0.52–0.90)	0.70	0.75
	External validation	0.75 (0.59–0.87)	0.85	0.65
ANN	Training cohort	1.00 (0.92–1.00)	1.00	1.00
	Internal validation	0.78 (0.62–0.94)	1.00	0.61
	External validation	0.90 (0.76–0.97)	1.00	0.80