
Handbook of Computational Intelligence in Biomedical Engineering and Healthcare
- 1st Edition - April 8, 2021
- Editors: Janmenjoy Nayak, Bighnaraj Naik, Danilo Pelusi, Asit Kumar Das
- Language: English
- Paperback ISBN:9 7 8 - 0 - 1 2 - 8 2 2 2 6 0 - 7
- eBook ISBN:9 7 8 - 0 - 1 2 - 8 2 2 2 6 1 - 4
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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Request a sales quoteHandbook 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.
- Presents a comprehensive handbook that covers an Introduction to Computational Intelligence in Biomedical Engineering and Healthcare, Computational Intelligence Techniques, and Advanced and Emerging Techniques in Computational Intelligence
- Helps readers analyze and do advanced research in specialty healthcare applications
- Includes links to websites, videos, articles and other online content to expand and support primary learning objectives
- Cover image
- Title page
- Table of Contents
- Copyright
- Contributors
- Biographies
- Preface
- Chapter 1. Application of dynamical systems based deep learning algorithms to model emergent characteristics for healthcare diagnostics
- 1. Introduction
- 2. Deep learning applications for brainwaves monitoring
- 3. Healthcare Modeling and simulation using feedback hybrid artificial neural networks
- 4. Derivative estimation using feedback networks
- 5. Usage of deep learning knowledge mining in Hybrid Inference Networks
- 6. Conclusions
- Chapter 2. Computational intelligence in healthcare and biosignal processing
- 1. Introduction
- 2. Investigation on various deep clustering algorithms
- 3. Investigation on clustering algorithms for the unsupervised learning methodology
- 4. Conclusion
- Chapter 3. A semi-supervised approach for automatic detection and segmentation of optic disc from retinal fundus image
- 1. Introduction
- 2. State-of-the-art
- 3. Proposed method
- 4. Experimentations and results
- 5. Conclusions
- Chapter 4. Medical decision support system using data mining: an intelligent health care monitoring system for guarded travel
- 1. Introduction
- 2. Related works
- 3. Proposed system
- 4. Performance analysis
- 5. Conclusion
- Chapter 5. Deep learning in gastroenterology: a brief review
- 1. Introduction
- 2. Anomalies in GI-tract and medical image modalities for GE
- 3. Conventional-ML in gastroenterology
- 4. DL based GI-tract diagnosis system
- 5. Critical analysis and discussions
- 6. Conclusion
- Chapter 6. Application of soft computing techniques to calculation of medicine dose during the treatment of patient: a fuzzy logic approach
- 1. Introduction
- 2. Soft computing
- 3. Fuzzy logic
- 4. Fuzzy logic based intelligent system
- 5. Comparison of drug doses suggested by expert doctor and proposed fuzzy based intelligent system
- 6. Conclusion
- Chapter 7. Multiobjective optimization technique for gene selection and sample categorization
- 1. Introduction
- 2. Gene subset selection
- 3. Results and discussions
- 4. Conclusion and future work
- Chapter 8. Medical decision support system using data mining semicircular-based angle-oriented facial recognition using neutrosophic logic
- 1. Introduction
- 2. Semicircular model based angle oriented images
- 3. Angle-oriented fuzzy rough sets
- 4. Ternary relationship with angle-oriented face recognition
- 5. K-means fuzzy rough angle-oriented clusters
- 6. Neutrosophic logic
- 7. Hyperplane
- 8. Evolutionary optimization method
- 9. Rotation and reduction procedure (R2 procedure)
- 10. Experimental result
- 11. Conclusion
- Chapter 9. Preservation module prediction by weighted differentially coexpressed gene network analysis (WDCGNA) of HIV-1 disease: a case study for cancer
- 1. Introduction
- 2. Related work
- 3. Material and methods
- 4. Result and analysis
- 5. KEGG pathway analysis
- 6. Conclusion
- Chapter 10. Computational intelligence for genomic data: a network biology approach
- 1. Introduction
- 2. Next generation sequencing overview
- 3. Different sequencing platforms
- 4. Different scores and parameters involved in biological network
- 5. Genomic data mining and biological network analysis: a case study
- 6. Summary and conclusions
- Chapter 11. A Kinect-based motor rehabilitation system for stroke recovery
- 1. Introduction
- 2. Literature survey
- 3. Proposed work
- 4. Experimental results
- 5. Conclusion and future work
- Chapter 12. Empirical study on Uddanam chronic kidney diseases (UCKD) with statistical and machine learning analysis including probabilistic neural networks
- 1. Introduction
- 2. Literature survey
- 3. Proposal model and materials
- 4. Results and discussions
- 5. Conclusion and social benefits
- Chapter 13. Enhanced brain tumor detection using fractional wavelet transform and artificial neural network
- 1. Introduction
- 2. Literature survey
- 3. Fractional wavelet transform
- 4. Principal component analysis
- 5. Artificial neural network
- 6. Proposed method
- 7. Experimental results
- 8. Conclusion
- Chapter 14. A study on smartphone sensor-based Human Activity Recognition using deep learning approaches
- 1. Introduction
- 2. Literature survey
- 3. Dataset description
- 4. Architecture of different deep networks
- 5. Results and discussion
- 6. Conclusion and future work
- Index
- No. of pages: 396
- Language: English
- Edition: 1
- Published: April 8, 2021
- Imprint: Academic Press
- Paperback ISBN: 9780128222607
- eBook ISBN: 9780128222614
JN
Janmenjoy Nayak
BN
Bighnaraj Naik
DP
Danilo Pelusi
AD