Table 2.

Summary of the classifiers developed, their input features and optimization criterion (F1-score or sensitivity). RF: random forest, ELM: extreme learning machine, K-nearest neighbors (KNN).

		RF		ELM		KNN
	Criterion	F1-Score	Sensitivity	F1-Score	Sensitivity	F1-Score	Sensitivity
Input Features
EHG 10th–90th percentiles + Obstetric data		RFF1_1	RFSEN_1	ELMF1_1	ELMSEN_1	KNNF1_1	KNNSEN_1
EHG 50th + Obstetric data		RFF1_2	RFSEN_2	ELMF1_2	ELMSEN_2	KNNF1_2	KNNSEN_2
EHG 10th–90th percentiles		RFF1_3	RFSEN_3	ELMF1_3	ELMSEN_3	KNNF1_3	KNNSEN_3
EHG 50th percentile		RFF1_4	RFSEN_4	ELMF1_4	ELMSEN_4	KNNF1_4	KNNSEN_4