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Handbook of Computational Intelligence in Biomedical Engineering and Healthcare helps readers analyze and conduct advanced research in specialty healthcare applications surroundi… Read more
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Immediately download your ebook while waiting for your print delivery. No promo code needed.
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.
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
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