Computational Learning Approaches to Data Analytics in Biomedical Applications provides a unified framework for biomedical data analysis using varied machine learning and statistical techniques. It presents insights on biomedical data processing, innovative clustering algorithms and techniques, and connections between statistical analysis and clustering. The book introduces and discusses the major problems relating to data analytics, provides a review of influential and state-of-the-art learning algorithms for biomedical applications, reviews cluster validity indices and how to select the appropriate index, and includes an overview of statistical methods that can be applied to increase confidence in the clustering framework and analysis of the results obtained.
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1. Introduction2. Data Preparation3. Clustering Algorithms4. Supervised learning5. Statistical Analysis tools and techniques6. Genomic Data Analysis7. Evaluation Metrics8. Visualization9. Bio informatics tools in MATLAB and Python
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Distinguishes theories and applications in computational learning as they relate to translational medicine
Includes an overview of data analytics in biomedical applications and current challenges
Updates on the latest research in supervised learning algorithms and applications, clustering algorithms and cluster validation indices
Provides complete coverage of computational and statistical analysis tools for biomedical data analysis
Presents hands-on training on the use of Python libraries, MATLAB® tools, WEKA, SAP-HANA and R/Bioconductor
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Produktdetaljer
ISBN
9780128144824
Publisert
2019-11-20
Utgiver
Vendor
Academic Press Inc
Vekt
790 gr
Høyde
235 mm
Bredde
191 mm
Aldersnivå
P, 06
Språk
Product language
Engelsk
Format
Product format
Innbundet
Antall sider
310