Deep Learning for Biomedical Data Analysis : Techniques, Approaches, and Applications
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Overview
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.
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Details
- ISBN-13: 9783030716752
- ISBN-10: 3030716759
- Publisher: Springer
- Publish Date: July 2021
- Dimensions: 9.21 x 6.14 x 0.81 inches
- Shipping Weight: 1.52 pounds
- Page Count: 359
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