| Description |
1 online resource (303 p.) |
| Series |
Intelligent Data-Centric Systems Series |
|
Intelligent Data-Centric Systems Series
|
| Contents |
Front Cover -- Diagnostic Biomedical Signal and Image Processing Applications With Deep Learning Methods -- Copyright Page -- Contents -- List of contributors -- 1 Introduction to deep learning and diagnosis in medicine -- Introduction -- Deep learning architectures -- Convolutional neural network -- AlexNet -- ZFNet -- NiN -- VGGNet -- Inception (GoogLeNet) -- ResNet -- DenseNet -- U-Net -- SegNet -- R-CNN -- YOLO -- Other convolutional neural networks algorithms -- Recurrent neural network -- Long short-term memory -- Gated recurrent unit -- Bidirectional recurrent neural network |
|
Boltzmann machine and restricted Boltzmann machines -- Autoencoder -- Generative adversarial network -- Semisupervised GAN, bidirectional GAN -- Conditional GAN, InfoGAN, AC-GAN -- LAPGAN, DCGAN, BEGAN -- SAGAN, BigGAN -- WGAN, WGAN-GP, LSGAN -- PROGAN, StyleGAN, StyleGAN2 -- Comparisons of some GAN models -- Other architectures -- Deep belief network -- Capsule network -- Hybrid architectures -- Application fields of deep learning in medicine -- Clinical and medical images -- Biosignals -- Biomedicine -- Electronic health records -- Other fields -- Conclusions -- References |
|
2 One-dimensional convolutional neural network-based identification of sleep disorders using electroencephalogram signals -- Introduction -- Materials and methods -- Dataset -- Method -- Results -- Discussions -- Conclusions -- References -- 3 Classification of histopathological colon cancer images using particle swarm optimization-based feature selection algorithm -- Introduction -- Methodology -- Dataset preparation -- Data preprocess and feature extraction -- Data size reduction -- Global feature extraction -- Classifier -- Gradient boosting -- Feature selection -- Particle swarm optimization |
|
Performance metrics -- Results -- Classification results -- Models complexity comparison -- SHAP analysis -- Receiver operator characteristic analysis -- Comparison -- Discussion -- Conclusion -- References -- 4 Arrhythmia diagnosis from ECG signal pulses with one-dimensional convolutional neural networks -- Introduction -- Definition of problem -- Materials and methods -- Dataset -- Oversampling -- 1D-CNN architecture -- 1D convolution layer -- Pooling layer -- Batch normalization and dropout layers -- Experimental result -- Performance metrics -- Experimental environment |
|
Random forest classifier -- 1D-CNN VGG16 classifier results -- Discussion -- Conclusion and future direction -- References -- 5 Patch-based approaches to whole slide histologic grading of breast cancer using convolutional neural networks -- Introduction and motivation -- Tubular formation -- Nuclear pleomorphism -- Mitotic figure detection and classification -- Challenges in obtaining Nottingham grading score -- Challenges in nuclear pleomorphism classification -- Challenges in detection/segmentation of tubular formation -- Challenges in mitotic classification |
| Notes |
Description based upon print version of record |
|
Literature review and state of the art |
| Form |
Electronic book
|
| Author |
Öztürk, Saban
|
| ISBN |
9780323996815 |
|
0323996817 |
|
