Machine Learning and Artificial Intelligence in Healthcare Systems: Tools and Techniques

This book combines engineering and medicine to advance healthcare treatment through machine learning and artificial intelligence. It discusses AI-based smart paradigms for infectious disease prediction, extended reality for healthcare applications, intelligent models for personal well-being services, computer-aided drug discovery, and big data and health analytics for improving healthcare delivery. Case studies illustrate the business processes behind these technologies. Contributions from experts in the field make it useful for healthcare professionals, researchers, and students in industrial engineering, systems engineering, biomedical engineering, computer science, electronics, and communications engineering.

Format: Hardback
Length: 350 pages
Publication date: 22 February 2022
Publisher: Taylor & Francis Ltd

This comprehensive book delves into the realm of machine learning and its applications in healthcare systems, aiming to bridge the gap between engineering and medicine. By seamlessly integrating design and problem-solving skills from engineering with the knowledge of health sciences, it strives to enhance healthcare treatment and improve patient outcomes.

Machine Learning and Artificial Intelligence in Healthcare Systems: Tools and Techniques explores the use of AI-based smart paradigms to accurately predict the dynamics of infectious diseases, thereby aiding in disease prevention. It sheds light on the diverse applications of extended reality in healthcare, highlighting the current state of research in this field. The book presents intelligent models for personalized well-being services, computer-aided drug discovery, and design methods. Case studies showcasing the business processes behind the utilization of big data and health analytics to enhance healthcare delivery take center stage. Additionally, innovative techniques for extracting user social behavior, known as sentiment analysis for healthcare-related purposes, are included to provide a well-rounded coverage of the diverse topics addressed in this reference book.

Contributions from esteemed experts in the field make this book invaluable for healthcare professionals, researchers, and students pursuing degrees in industrial engineering, systems engineering, biomedical engineering, computer science, electronics, and communications engineering. By unraveling the complexities of machine learning and its practical applications in healthcare, this book empowers professionals to drive innovation and improve the quality of healthcare services.

Dimension: 234 x 156 (mm)
ISBN-13: 9781032208305