Predictive Intelligence in Biomedical and Health Informatics / / ed. by Rajshree Srivastava, Siddhartha Bhattacharyya, Ashish Khanna, Nhu Gia Nguyen.
Predictive Intelligence in Biomedical and Health Informatics focuses on imaging, computer-aided diagnosis and therapy as well as intelligent biomedical image processing and analysis. It develops computational models, methods and tools for biomedical engineering related to computer-aided diagnostics...
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Superior document: | Title is part of eBook package: De Gruyter DG Ebook Package English 2020 |
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MitwirkendeR: | |
HerausgeberIn: | |
Place / Publishing House: | Berlin ;, Boston : : De Gruyter, , [2020] ©2020 |
Year of Publication: | 2020 |
Language: | English |
Series: | Intelligent Biomedical Data Analysis ,
2 |
Online Access: | |
Physical Description: | 1 online resource (XIV, 166 p.) |
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Other title: | Frontmatter -- Preface -- Contents -- List of contributors -- 1. Smart connected devices reforming the healthcare sector -- 2. An ample review on brain image classification for Alzheimer’s disease -- 3. Innovations in biological applications with machine learning -- 4. Wavelet applications in medical image processing -- 5. Nanomedicine strategies: a precise therapeutic approach for disease -- 6. Optimal placement of body node coordinator in wireless body area network using genetic algorithm -- 7. Drug discovery -- 8. Smart health care service evolution with Internet of things -- Index |
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Summary: | Predictive Intelligence in Biomedical and Health Informatics focuses on imaging, computer-aided diagnosis and therapy as well as intelligent biomedical image processing and analysis. It develops computational models, methods and tools for biomedical engineering related to computer-aided diagnostics (CAD), computer-aided surgery (CAS), computational anatomy and bioinformatics. Large volumes of complex data are often a key feature of biomedical and engineering problems and computational intelligence helps to address such problems. Practical and validated solutions to hard biomedical and engineering problems can be developed by the applications of neural networks, support vector machines, reservoir computing, evolutionary optimization, biosignal processing, pattern recognition methods and other techniques to address complex problems of the real world. |
Format: | Mode of access: Internet via World Wide Web. |
ISBN: | 9783110676129 9783110696288 9783110696271 9783110704716 9783110704518 9783110704815 9783110704617 |
ISSN: | 2629-7140 ; |
DOI: | 10.1515/9783110676129 |
Access: | restricted access |
Hierarchical level: | Monograph |
Statement of Responsibility: | ed. by Rajshree Srivastava, Siddhartha Bhattacharyya, Ashish Khanna, Nhu Gia Nguyen. |