Deep Learning, Machine Learning and IoT in Biomedical and Health Informatics: Techniques and Applications

Biomedical and Health Informatics is an important field that brings opportunities and helps address challenges due to an abundance of available biomedical data. This book examines and demonstrates state-of-the-art approaches for IoT and Machine Learning based biomedical and health related applications. It aims to provide computational methods for accumulating, updating and changing knowledge in intelligent systems and particularly learning mechanisms that help us to induce knowledge from the data. Intelligent IoT systems have demonstrated great performance to a variety of areas, including big data analytics, time series, biomedical and health informatics.

Format: Hardback
Length: 362 pages
Publication date: 11 February 2022
Publisher: Taylor & Francis Ltd

Biomedical and Health Informatics is a crucial domain that presents immense prospects and facilitates the resolution of challenges stemming from the vast abundance of biomedical data available. This comprehensive book delves into and showcases cutting-edge methodologies for IoT and Machine Learning-based applications in the biomedical and health sectors. Its primary objective is to offer computational techniques for the accumulation, updating, and modification of knowledge in intelligent systems, particularly learning mechanisms that enable the extraction of knowledge from data. This book proves invaluable in scenarios where direct algorithmic solutions are unavailable, formal models are lacking, or the knowledge about the application domain is insufficiently defined.

Looking ahead, the IoT holds the potential to revolutionize the way we work and interact with the world. These computing methodologies also hold significant importance in the fields of design and optimization across various engineering disciplines. As the concept of IoT continues to gain traction and evolve, the demand for AI (artificial intelligence) techniques has grown increasingly significant. The primary aim of these techniques is to embrace imprecision, uncertainty, and approximations to expedite the development of solutions. However, recent advancements in the representation of intelligent IoT systems have led to the creation of more intelligent and robust systems that offer human-interpretable, cost-effective, and approximate solutions.

Intelligent IoT systems have demonstrated exceptional performance across diverse domains, including big data analytics, time series, and biomedical and health informatics. This book serves as a valuable resource for both novice researchers and practitioners in the biomedical and healthcare fields, providing them with a comprehensive understanding of the most effective methods. It is also suitable for a wide range of readers, including individuals who may not possess scientific backgrounds but have a keen interest in the practical applications of these technologies.

Weight: 702g
Dimension: 160 x 241 x 29 (mm)
ISBN-13: 9780367544256