Table 3. The mean performance of different fusion strategies based on the ResNet18 model in the validation set.

Model	ACC	AUC	F1	SEN	SPE	BACC	P
Late fusion	0.770±0.040	0.724±0.078	0.649±0.095	0.571±0.182	0.900±0.070	0.736±0.063	0.144
Score fusion	0.770±0.045	0.733±0.066	0.662±0.111	0.621±0.229	0.870±0.107	0.746±0.072	0.255
Our model	0.820±0.024	0.795±0.068	0.760±0.050	0.746±0.121	0.869±0.044	0.808±0.040	–

Data are presented as mean ± SD. ACC, accuracy; AUC, area under the curve; BACC, balanced accuracy; F1, F1-score; SD, standard deviation; SEN, sensitivity; SPE, specificity.