Handbook of Computational Intelligence in Biomedical Engineering and Healthcare helps readers analyze and conduct advanced research in specialty healthcare applications surrounding oncology, genomics and genetic data, ontologies construction, bio-memetic systems, biomedical electronics, protein structure prediction, and biomedical data analysis. The book provides the reader with a comprehensive guide to advanced computational intelligence, spanning deep learning, fuzzy logic, connectionist systems, evolutionary computation, cellular automata, self-organizing systems, soft computing, and hybrid intelligent systems in biomedical and healthcare applications. Sections focus on important biomedical engineering applications, including biosensors, enzyme immobilization techniques, immuno-assays, and nanomaterials for biosensors and other biomedical techniques.
Other sections cover gene-based solutions and applications through computational intelligence techniques and the impact of nonlinear/unstructured data on experimental analysis.
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Table of Contents
Part 1: Computational Intelligence in Bioengineering and Health Care: An Introduction 1. Data Analysis in Bioengineering and Health Care: Advances and Challenges 2. Impact of Data Type and Analysis on Nature of Data 3. Computational Intelligence in Healthcare: Real Life Applications
Part 2: Computational Intelligence Techniques 4. Computational Intelligence: Past to Present 5. Computational Intelligence: Methods�and Tools 6. Computational Intelligence: Trends and Applications 7. Computational Intelligence: Issues and Future Challenges
Part 3: Computational Intelligence in Bioengineering: A step towards the Next 8. Advance Computational Intelligence Techniques in bioengineering 9. A Case Study 10. New Technologies for biosensors 11. Performance Analysis: Statistical Approach