Deep Learning for Biomedical Data Analysis : Techniques, Approaches, and Applications /
This book is the first overview on Deep Learning (DL) for biomedical data analysis. It surveys the most recent techniques and approaches in this field, with both a broad coverage and enough depth to be of practical use to working professionals. This book offers enough fundamental and technical infor...
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| Format: | eBook |
| Language: | English |
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Cham :
Springer International Publishing : Imprint: Springer,
2021.
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| Edition: | 1st ed. 2021. |
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| Online Access: | Connect to the full text of this electronic book |
Table of Contents:
- 1-Dimensional Convolution Neural Network Classification Technique for Gene Expression Data
- Classification of Sequences with Deep Artificial Neural Networks: Representation and Architectural Issues
- A Deep Learning Model for MicroRNA-Target Binding
- Recurrent Neural Networks Architectures for Accidental Fall Detection on Wearable Embedded Devices
- Medical Image Retrieval System using Deep Learning Techniques
- Medical Image Fusion using Deep Learning
- Deep Learning for Histopathological Image Analysis
- Innovative Deep Learning Approach for Biomedical Data Instantiation and Visualization
- Convolutional Neural Networks in Advanced Biomedical Imaging Applications
- Deep Learning for Lung Disease Detection from Chest X-Rays Images
- Deep Learning in Multi-Omics Data Integration in Cancer Diagnostic
- Using Deep Learning with Canadian Primary Care Data for Disease Diagnosis
- Brain Tumor Segmentation and Surveillance with Deep Artificial Neural Networks.