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.
Key Features
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
Readership
Graduates, PhD students and lecturers in computer science, biomedical engineering and electrical engineering, as well as scientific researchers in biomedical fields and clinicians
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
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.
Affiliations and Expertise
Associate Professor, Department of Computer Science and Engineering, Aditya Institute of Technology and Management, India
Bighnaraj Naik
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 reputed peer reviewed International Journals, Conferences and Book Chapters. He has edited ten books from various international publishers such as Elsevier, Springer and IGI Global. At present, he has more than ten years of teaching experience in the field of Computer Science and Information Technology. He is a member of IEEE and his area of interest includes Data Science, Data Mining, Machine Learning, Deep Learning, Computational Intelligence and its applications in Science and Engineering. He has been serving as Guest Editor of various journal special issues in 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) etc. He is an active reviewer of various reputed journals from reputed publishers including IEEE Transactions, Elsevier, Springer and Inderscience etc. Currently, he is undertaking a major research project in the capacity of Principal Investigator, which is funded by Science and Engineering Research Board (SERB), Dept. of Science & Technology (DST), Govt. of India.
Affiliations and Expertise
Assistant Professor, Department of Computer Application, Veer Surrendra Sai University of Technology, Burla, India
Danilo Pelusi
Danilo Pelusi received the degree in Physics from the University of Bologna (Italy) and the Ph.D. degree in Computational Astrophysics from the University of Teramo (Italy). Currently, he is an Associate Professor of Computer Science at the Department of Communication Sciences, University of Teramo. Editor of Springer and Elsevier books and Associate Editor of IEEE Transactions on Emerging Topics in Computational Intelligence (2017-2020), IEEE Access (2018-present) and IEEE Transactions on Neural Networks and Learning Systems (2022-present), he is Guest Editor for Elsevier, Springer, MDPI and Hindawi journals. Keynote speaker, Guest of Honor and Chair of IEEE conferences, he is inventor of patents on Artificial Intelligence. His research interests include Fuzzy Logic, Neural Networks, Information Theory, Machine Learning and Evolutionary Algorithms.
Affiliations and Expertise
Associate Professor, Faculty of Communication Sciences, University of Teramo, Teramo, Italy
Asit Kumar Das
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.
Affiliations and Expertise
Indian Institute of Engineering Science and Technology, Shibpur, India
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