From: Sch-net: a deep learning architecture for automatic detection of schizophrenia
Method | Accuracy | Precision | Recall | F1-score | |
---|---|---|---|---|---|
State-of-the-art method | 0.9694 | 1.0000 | 0.9474 | 0.9730 | |
Ramarao [88] | 0.9941 | - | - | - | |
Slogrove [89] | 0.9800 | 0.9900 | 0.9900 | 0.9900 | |
Sharma [90] | 0.9790 | - | - | - | |
Reddy [91] | 0.9882 | - | - | - | |
Deep Neural Network | AlexNet | 0.9132 | 0.9585 | 0.8810 | 0.9181 |
VGG16 | 0.9230 | 0.9897 | 0.8787 | 0.9309 | |
ResNet34 | 0.9329 | 0.9489 | 0.9286 | 0.9386 | |
DenseNet121 | 0.9461 | 0.9397 | 0.9643 | 0.9518 | |
Xception | 0.9622 | 0.9514 | 0.9863 | 0.9685 | |
Sch-net (our) | 0.9952 | 0.9979 | 0.9937 | 0.9958 |