Handbook of Computational Intelligence in Biomedical Engineering and Healthcare - Softcover

Über die Autorinnen und Autoren

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.

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.

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.

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.

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In spite of many advancements, the Editors of Handbook of Computational Intelligence in Biomedical Engineering and Healthcare believe that machines (intelligent computing methods) cannot replace human physicians in the future of healthcare, but they can definitely assist physicians to make better clinical decisions or even replace human judgement in certain functional areas. This book reveals different dimensions of computational intelligence applications and illustrates its use in the solution of a variety of real world biomedical and healthcare problems. Moreover, the book also covers distinctive algorithms and techniques in areas including cancer classification and prediction, medical imaging, bio-modelling, structured and unstructured clinical reports, X-ray and biosignal analysis. The book helps readers to analyze and do advance research in specialty healthcare applications such as 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 the areas of deep learning, fuzzy logic, connectionist systems, evolutionary computation, cellular automata, self-organizing systems, soft computing, and hybrid intelligent systems in biomedical and healthcare applications.

Computational Intelligence in Biomedical Engineering and Healthcare focuses on important biomedical engineering applications such as biosensors, enzyme immobilization techniques, immuno-assays, and nanomaterials for biosensor and other biomedical techniques. The book includes a special focus on gene-based solutions and applications through computational intelligence techniques. The impact of nonlinear/unstructured data on experimental analysis is covered to provide using advanced methods and solutions. The book includes a special focus on advanced deep learning methods to solve medical and healthcare problems and provides case studies illustrating the applications of intelligent computing in data analysis.