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Table 3 Results of evaluation using independent test data with a size of 21 tissue samples patches equally distributed at the checkpoint after 254 epochs with lowest loss of 0.1321 as shown in Fig. 6. Values are reported as class-dependent classification scores (Acc = accuracy, Spec = specificity, Sens = sensitivity)

From: Hyperspectral imaging and artificial intelligence to detect oral malignancy – part 1 - automated tissue classification of oral muscle, fat and mucosa using a light-weight 6-layer deep neural network

Class Samples Acc Spec Sens
Fat 7 0.95 1.00 0.86
Muscle 7 0.86 0.79 1.00
Mucosa 7 0.81 0.93 0.57