Table 3.

Comparison of performance in the multimodal ACNN model and preoperative CNB for predicting four-classification molecular subtypes of breast cancers.

Methods	Datasets	AUC	Sensitivity (%)	Specificity (%)	Accuracy (%)
Multimodal ACNN model	Internal validation cohort (n=37)	0.89	84.87	82.47	83.73
	Test cohort A (n=42)	0.92	83.00	81.35	83.33
	Test cohort B (n=24)	0.99	89.62	76.27	83.33
Preoperative CNB	Internal validation cohort (n=37)	0.67	51.56	49.70	64.86
	Test cohort A (n=42)	0.74	61.11	70.93	66.67
	Test cohort B (n=24)	0.82	49.66	63.54	62.50

Note. —The multimodal ACNN model was trained and tested with greyscale US and CDFI as well as SWE images.

ACNN, assembled convolutional neural network; AUC, area under the receiver operating characteristic curve; CNB, core needle biopsy.