[Retracted] Automatic Detection of High-Frequency Oscillations Based on an End-to-End Bi-Branch Neural Network and Clinical Cross-Validation

Table 5

The results for the bi-branch feature fusion model using cross-subject validation.

Group	Confusion matrix						Evaluation metrics (%)
	TN	FP	FN	TP	SEN	SPE	PRE	ACC	FDR	F1	SEN_SPE
1	838	132	50	675	93.10	86.39	83.64	89.26	16.36	88.12	89.62
2	954	109	120	780	86.67	89.75	87.74	88.33	12.26	87.20	88.18
3	865	256	30	783	96.31	77.16	75.36	85.21	24.64	84.56	85.68
4	2282	61	41	2370	98.30	97.40	97.49	97.85	2.51	97.89	97.85
5	2642	274	418	2487	85.61	90.60	90.08	88.11	9.92	87.79	88.04
Average					92.00	88.26	86.86	89.76	13.14	89.11	89.87