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

Table 4

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

Group	Confusion matrix						Evaluation metrics (%)
	TN	FP	FN	TP	SEN	SPE	PRE	ACC	FDR	F1	SEN_SPE
1	698	57	34	657	95.08	92.45	92.02	93.71	7.98	93.52	93.75
2	692	49	47	631	93.07	93.39	92.79	93.23	7.21	92.93	93.23
3	675	69	21	657	96.90	90.73	90.50	93.67	9.50	93.59	93.71
4	1232	130	74	1126	93.83	90.46	89.65	92.04	10.35	91.69	92.11
5	546	20	27	440	94.22	96.47	95.65	95.45	4.35	94.93	95.33
Average					94.62	92.70	92.12	93.62	7.88	93.33	93.63