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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