Main description:

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.

Contents:

1. Introduction 2. Data Preparation 3. Clustering Algorithms 4. Supervised learning 5. Statistical Analysis tools and techniques 6. Genomic Data Analysis 7. Evaluation Metrics 8. Visualization 9. Bio informatics tools in MATLAB and Python