Machine Learning and Analytics in Healthcare Systems: Principles and Applications

The book aims to bridge the gap between engineering and medicine by applying machine learning to healthcare systems, offering real-world case studies and multiple perspectives on various disciplines. It can be used as a reference for practitioners, researchers, and students in Computer Science, Electronics, and Communications.

Format: Paperback / softback
Length: 276 pages
Publication date: 01 July 2021
Publisher: CRC Press

Machine learning (ML) has the potential to revolutionize healthcare systems by improving diagnosis, monitoring, and therapy. However, there is a significant gap between engineering and medicine that needs to be bridged in order to fully realize the benefits of ML in healthcare. This book aims to close this gap by combining the design and problem-solving skills of engineering with the health sciences. The book will cover a wide range of areas, including diagnosis, monitoring, and therapy, and will include real-world case studies to illustrate the applications of ML in healthcare systems. It will also provide a detailed exploration of applications in healthcare systems, offer multiple perspectives on a variety of disciplines, and let the reader know how to avoid some of the consequences of old methods with data sharing. The book can be used as a reference for practitioners, researchers, and students at basic and intermediary levels in Computer Science, Electronics and Communications.

Weight: 390g
Dimension: 234 x 156 x 15 (mm)
ISBN-13: 9780367564865