Deep Learning for Data Analytics: Foundations, Biomedical Applications, and Challenges 1st Edition Himansu Das 0128226080 9780128226087

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Product details:

• ISBN 10: 0128226080
• ISBN 13: 9780128226087
• Author: Himansu Das

Deep learning, a branch of Artificial Intelligence and machine learning, has led to new approaches to solving problems in a variety of domains including data science, data analytics and biomedical engineering. Deep Learning for Data Analytics: Foundations, Biomedical Applications and Challenges provides readers with a focused approach for the design and implementation of deep learning concepts using data analytics techniques in large scale environments. Deep learning algorithms are based on artificial neural network models to cascade multiple layers of nonlinear processing, which aids in feature extraction and learning in supervised and unsupervised ways, including classification and pattern analysis. Deep learning transforms data through a cascade of layers, helping systems analyze and process complex data sets. Deep learning algorithms extract high level complex data and process these complex sets to relatively simpler ideas formulated in the preceding level of the hierarchy

Table of contents:

1. Short and noisy electrocardiogram classification based on deep learning

2. Single-layer convolution neural network for cardiac disease classification using electrocardiogra

3. Generalization performance of deep autoencoder kernels for identification of abnormalities on ele

4. Deep learning for early diagnosis of Alzheimer’s disease: a contribution and a brief review

5. Musculoskeletal radiographs classification using deep learning

6. Deep-wavelet neural networks for breast cancer early diagnosis using mammary termographies

7. Deep learning on information retrieval and its applications

8. Electrical impedance tomography image reconstruction based on autoencoders and extreme learning m

9. Crop disease classification using deep learning approach: an overview and a case study

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