Table 6. Performance of DAPPER framework for VGG backend network, and classifier heads (FCH, SVM, RF) on KIMIA24 dataset.

The average cross validation MCC (K24-MCCt), and ACC (K24-ACCt) with 95% CI, as well as MCC (K24-MCCv), and ACC (K24-ACCv) on external validation set are reported.

Model	K24-MCCt	K24-MCCv	K24-ACCt	K24-ACCv
VGG+FCH	0.317 (0.306, 0.327)	0.207	34.4 (33.2, 35.2)	23.8
VGG+SVM	0.446 (0.439, 0.454)	0.409	47.1 (46.4, 47.8)	43.4
VGG+RF	0.457 (0.449, 0.465)	0.409	48.0 (47.3, 48.8)	43.4