Handbook of Computational Intelligence in Biomedical Engineering and Healthcare

Erscheinungsjahr 2021
ISBN: 978-0-12-822260-7
Verlag: William Andrew Publishing

Buch, Englisch, 396 Seiten, Format (B × H): 191 mm x 235 mm, Gewicht: 820 g

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.

Autoren/Hrsg.

Nayak, Janmenjoy

Naik, Bighnaraj

Pelusi, Danilo

Das, Asit Kumar

Fachgebiete

• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizintechnik, Biomedizintechnik, Medizinische Werkstoffe
• Technische Wissenschaften Sonstige Technologien | Angewandte Technik Medizintechnik, Biomedizintechnik

Inhaltsverzeichnis

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

Über Autor(innen)

Naik, Bighnaraj
Bighnaraj Naik is an Assistant Professor in the Department of Computer Application, Veer Surendra Sai University of Technology (formerly UCE Burla), Odisha, India. He has published more than 100 research articles in various peer reviewed international journals, conferences, and book chapters. He has edited 10 books for publishers including Elsevier, Springer, and IGI Global. At present, he has more than 10 years of teaching experience in the field of computer science and information technology. He is a member of the Institute of Electrical and Electronics Engineers (IEEE) and his areas of interest include data science, data mining, machine learning, deep learning, computational intelligence (CI), and CI's applications in science and engineering. He has served as Guest Editor of various special issues of journals such as Information Fusion (Elsevier), Neural Computing and Applications (Springer), Evolutionary Intelligence (Springer), International Journal of Computational Intelligence Studies (Inderscience), and International Journal of Swarm Intelligence (Inderscience). He is an active reviewer of various journals from publishers including IEEE Transactions, Elsevier, Springer, and Inderscience. Currently, he is undertaking a major research project as Principal Investigator, which is funded by the Science and Engineering Research Board (SERB), Department of Science and Technology (DST), Government of India.

Nayak, Janmenjoy
Dr. Janmenjoy Nayak is an Associate Professor in the Department of Computer Science and Engineering at Aditya Institute of Technology and Management, India. He has presented over 100 research articles in reputed international journals, conferences and books.

Pelusi, Danilo
Danilo Pelusi is an Associate Professor in the Department of Communication Sciences, University of Teramo, where he received his PhD in Computational Astrophysics. He is an Editor of books for Springer and Elsevier, and an Associate Editor of IEEE Transactions on Emerging Topics in Computational Intelligence, and IEEE Access, and was an Associate Editor of International Journal of Machine Learning and Cybernetics. He is a Guest Editor for Elsevier, Springer, and Inderscience journals and keynote speaker in several IEEE conferences; he is also an editorial board member of many journals. His research interests include fuzzy logic, neural networks, information theory, machine learning, and evolutionary algorithms.

Das, Asit Kumar
Asit Kumar Das is Professor of Computer Science and Technology, at the Indian Institute of Engineering Science and Technology Shibpur, Howrah. He is also the Head of the Center of Healthcare Science and Technology of the Institute. His area of research interest includes data mining and pattern recognition, social networks, bioinformatics, machine learning and soft computing, text, audio and video data analysis.