Computational Intelligence in Biomedical Internet of Medical Things

Through comprehensive insights and real-world case studies, this book features in-depth knowledge of key concepts relating to optimizing biomedical IoMT systems.

Biomedical Internet of Medical Things is a technological paradigm encompassing a range of technologies that enable machines to mimic human intelligence. Machine and deep learning algorithms facilitate self-learning for the discovery of hidden patterns, associations, and risks from voluminous datasets. Computer vision and natural language processing are prominent applications of AI, allowing machines to see and understand the world in ways previously only possible for humans. In healthcare, generative techniques can analyze large and complex datasets from wearable sensors, identifying patterns and trends that can aid in detecting, diagnosing, and monitoring chronic diseases. This book comprehensively consolidates the latest technologies, groundbreaking research, and practical applications of computational intelligence in biomedical IoMT, with a strong emphasis on optimizing healthcare information systems.

Readers will find the volume:

• Explores the transformative role of computational intelligence in the Internet of Medical Things (IoMT), demonstrating how intelligent systems enhance healthcare efficiency, accuracy, and patient-centric solutions at various scales;
• Examines key computational intelligence techniques and algorithms used in modern biomedical IoMT applications, emphasizing their impact on real-time diagnostics, personalized treatment, and remote patient monitoring;
• Highlights the evolution of AI-driven paradigms in biomedical IoMT, showcasing their role in predictive analytics, automated decision-making, and adaptive healthcare systems;
• Investigates the integration of trust management and advanced cybersecurity frameworks in intelligent healthcare networks.

Audience

Academics, research scholars, and industry professionals in the fields of mathematics, computer science, information technology, and health science.

Satya Prakash Yadav, PhD is an Associate Professor in the Department of Computer Science and Engineering, Madan Mohan Malaviya University of Technology, Gorakhpur, U.P., India with more than 17 years of experience. He has published four books, two patents, and many research articles in international journals and conferences. His research focuses on image processing, information retrieval, and feature extraction and programming.

Abhay Bansal, PhD is a Professor and the Dean of the School of Computer Science Engineering and Technology and the Dean of International Affairs and Corporate Outreach, Bennett University, Greater Noida , UP, India with more than 29 years of research and teaching experience. He has published more than 130 papers in various international journals and conferences of repute. His research interests include data science, data analytics, cloud computing, and data structure.

Victor Hugo C. de Albuquerque, PhD is a Professor and Senior Researcher in the Department of Teleinformatics Engineering, Federal University of Ceará, Brazil. He is a full member of the Brazilian Society of Biomedical Engineering and serves as an editor for several international journals and conferences. He has experience in biomedical science and engineering, mainly in the fields of applied computing, intelligent systems, and visualization and interaction.