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books
| book details |
Signal Processing Driven Machine Learning Techniques for Cardiovascular Data Processing
Edited by Rajesh Kumar Tripathy, Edited by Ram Bilas Pachori
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normal price: R 6 778.95
Price: R 6 440.95
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| book description |
Signal Processing Driven Machine Learning Techniques for Cardiovascular Data Processing features recent advances in machine learning coupled with new signal processing-based methods for cardiovascular data analysis. Topics in this book include machine learning methods such as supervised learning, unsupervised learning, semi-supervised learning, and meta-learning combined with different signal processing techniques such as multivariate data analysis, time-frequency analysis, multiscale analysis, and feature extraction techniques for the detection of cardiovascular diseases, heart valve disorders, hypertension, and activity monitoring using ECG, PPG, and PCG signals. In addition, this book also includes the applications of digital signal processing (time-frequency analysis, multiscale decomposition, feature extraction, non-linear analysis, and transform domain methods), machine learning and deep learning (convolutional neural network (CNN), recurrent neural network (RNN), transformer and attention-based models, etc.) techniques for the analysis of cardiac signals. The interpretable machine learning and deep learning models combined with signal processing for cardiovascular data analysis are also covered.
| product details |
Normally shipped |
Publisher | Elsevier Science Publishing Co Inc
Published date | 18 Jun 2024
Language |
Format | Paperback / softback
Pages | 184
Dimensions | 229 x 152 x 0mm (L x W x H)
Weight | 300g
ISBN | 978-0-4431-4141-6
Readership Age |
BISAC | medical / cardiology
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Katie Daysh
Paperback / softback
384 pages
was: R 295.95
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