Table 3.

Skin lesion management prediction results ${\mathrm{MGMT}}_{\mathrm{pred},\mathrm{multi}}$ obtained using a multi-modal multi-task model.

Management labels	Metrics
	Sensitivity	Specificity	Precision	AUROC	Overall accuracy
NONE	0.6500	0.9747	0.7429	0.9225	–
CLNC	0.6071	0.8375	0.5965	0.8065	–
EXC	0.8107	0.6776	0.8008	0.8226	–
Average	0.6893	0.8299	0.7134	0.8505	0.7367
3-Fold cross validation	0.6528 ± 0.0477	0.8215 ± 0.0094	0.7123 ± 0.0114	0.8449 ± 0.0135	0.7301 ± 0.0150

All the prediction models have been trained using all the input data modalities (i.e., clinical image, dermoscopic image, and patient metadata). Mean ± standard deviation reported for all the metrics for the 3-fold cross validation.