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Table 2 Performance comparison between deep learning vs. non-deep learning based approaches

From: Analyzing MRI scans to detect glioblastoma tumor using hybrid deep belief networks

Classification techniques

Accuracy

Specificity

Sensitivity

F-score

MLP

0.85 ± 0.33

0.83 ± 0.26

0.87 ± 0.22

0.84 ± 0.30

RNN

0.87 ± 0.23

0.88 ± 0.31

0.85 ± 0.21

0.84 ± 0.29

RBFNN

0.79 ± 0.22

0.75 ± 0.23

0.74 ± 0.34

0.74 ± 0.21

ELM

0.90 ± 0.15

0.87 ± 0.32

0.91 ± 0.22

0.89 ± 0.25

PNN

0.89 ± 0.18

0.90 ± 0.28

0.87 ± 0.29

0.88 ± 0.32

TDNN

0.86 ± 0.32

0.85 ± 0.25

0.88 ± 0.23

0.86 ± 0.29

DWT-PCA-DBN

0.95 ± 0.14

0.94 ± 0.16

0.97 ± 0.26

0.95 ± 0.15