Table 3 Classifier outcome of MFFDCNN-CTDC model on HAM10000 database.

From: Multi-scale feature fusion of deep convolutional neural networks on cancerous tumor detection and classification using biomedical images

Class Labels

\(Acc{u}_{y}\)

\(Sen{s}_{y}\)

\(Spe{c}_{y}\)

\({F}_{score}\)

\(MCC\)

70% TRAPH

 AKIEC

99.31

87.91

99.66

88.52

88.17

 BCC

99.04

88.60

99.64

90.96

90.48

 BKL

98.92

94.90

99.41

95.02

94.42

 DF

99.63

88.46

99.80

87.62

87.44

 NV

98.02

98.94

96.13

98.53

95.50

 MEL

98.97

96.03

99.32

95.21

94.64

 VASC

99.26

60.19

99.84

70.45

71.16

 Average

99.02

87.86

99.12

89.47

88.83

30% TESPH

 AKIEC

99.04

85.71

99.55

86.88

86.39

 BCC

98.84

87.10

99.48

88.52

87.93

 BKL

98.91

94.93

99.41

95.07

94.45

 DF

99.64

80.39

99.97

88.17

88.42

 NV

97.85

98.84

96.00

98.36

95.25

 MEL

98.55

94.96

99.03

93.91

93.09

 VASC

99.37

64.10

99.83

72.46

72.79

 Average

98.89

86.58

99.04

89.05

88.33