Computational Intelligence and Blockchain in Biomedical and Health Informatics (Paperback)

Advancements in computational intelligence, which encompasses artificial intelligence, machine learning, and data analytics, have revolutionized the way we process and analyze biomedical and health data. These techniques offer novel approaches to understanding complex biological systems, improving disease diagnosis, optimizing treatment plans, and enhancing patient outcomes. Computational Intelligence and Blockchain in Biomedical and Health Informatics introduces the role of computational intelligence and blockchain in the biomedical and health informatics fields and provides a framework and summary of the various methods. The book emphasizes the role of advanced computational techniques and offers demonstrative examples throughout. Techniques to analyze the impacts on the biomedical and health Informatics domains are discussed along with major challenges in deployment. Rounding out the book are highlights of the transformative potential of computational intelligence and blockchain in addressing critical issues in healthcare from disease diagnosis and personalized medicine to health data management and interoperability along with two case studies. This book is highly beneficial to educators, researchers, and anyone involved with health data.

Features:

• Introduces the role of computational intelligence and blockchain in the biomedical and health informatics fields.

• Provides a framework and a summary of various computational intelligence and blockchain methods.

• Emphasizes the role of advanced computational techniques and offers demonstrative examples throughout.

• Techniques to analyze the impact on biomedical and health informatics are discussed along with major challenges in deployment.

• Highlights the transformative potential of computational intelligence and blockchain in addressing critical issues in healthcare from disease diagnosis and personalized medicine to health data management and interoperability.

Dr. Pankaj Bhambri works in the Department of Information Technology at Ludhiana’s Guru Nanak Dev Engineering College. He serves as the Institute’s Coordinator, Skill Enhancement Cell, and has almost two decades of teaching experience. He earned his M.Tech. (CSE) and a B.E. (IT) with honors from the I.K.G. Punjab Technical University, Jalandhar, India, and Dr. B.R. Ambedkar University, Agra, India, respectively. Dr. Bhambri earned his doctorate in computer science and engineering from the I.K.G. Punjab Technical University, Jalandhar, India. His research has appeared in a variety of prestigious international/national journals and conference proceedings and he has contributed to numerous books and has also filed several patents. Dr. Bhambri has been awarded the ISTE Best Teacher Award in 2023 and 2022, the I2OR National Award in 2020, the Green ThinkerZ Top 100 International Distinguished Educators in 2020, the I2OR Outstanding Educator Award in 2019, the LCHC Best Teacher Award in 2007, the CIPS Rashtriya Rattan Award in 2008, and the SAA Distinguished Alumni Award in 2012 along with countless other accolades from various government and non-profit organizations. Machine Learning, Bioinformatics, Wireless Sensor Networks, and Network Security are his areas of interest.

Dr. Sita Rani is working as an Assistant Professor in the Department of Computer Science and Engineering at Guru Nanak Dev Engineering College, Ludhiana. She has served as Deputy Dean (Research) at Gulzar Group of Institutions, Khanna (Punjab). Dr. Rani completed her B.Tech and M.Tech degrees in the faculty of Computer Science and Engineering from Guru Nanak Dev Engineering College, Ludhiana. She earned her Ph.D. in Computer Science and Engineering from I.K.Gujral Punjab Technical University, Kapurthala, Punjab in the year 2018 and has more than 19 years of teaching experience. She is the receiver of ISTE Section Best Teacher Award- 2020, and International Young Scientist Award-2021. She has contributed to various research activities while publishing articles in renowned journals and conference proceedings. She has three international patents to her credit as well. Her research interest includes Parallel and Distributed Computing, Machine Learning, and the Internet of Things (IoT).

Dr. Muhammad Fahim is a Lecturer (Assistant Professor) in AI theme at the School of Electronics, Electrical Engineering and Computer Science (EEECS), Queen's University Belfast, and a member of the Centre for Data Sciences and Scalable Computing (DSSC), and hold a fellowship Global Institute for Innovation. Fahim worked as an Assistant Professor at the Institute of Data Science and Artificial Intelligence, Innopolis University, Russia from Sept. 2017 to June 2021. He also served as an Assistant Professor in the Department of Computer Engineering at Istanbul Sabahattin Zaim University, Istanbul, Turkey, and led a machine learning research lab for 3 years (i.e., Sept. 2014 to Aug. 2017). Fahim earned Ph.D. in Artificial Intelligence and made a significant contribution to the ubiquitous lifecare research center in Seoul, South Korea. His contributions to this field are based on the design and development of novel machine-learning models to process the sensory data streams collected in smart environments including smart homes, buildings, and wearables.