Machine Learning and Artificial Intelligence in Healthcare Systems

This book highlights the role of machine learning in healthcare, showcasing innovative applications and bridging engineering with medical sciences for better treatment outcomes.

This book explores the integration of machine learning and artificial intelligence within healthcare systems, aiming to bridge the gap between engineering and medicine. By combining the design and problem-solving skills of engineering with the health sciences, Machine Learning and Artificial Intelligence in Healthcare Systems seeks to advance healthcare treatment and improve patient outcomes. The text emphasizes the importance of collaboration between these fields to foster innovative solutions that can enhance the quality of care provided to patients.

In Machine Learning and Artificial Intelligence in Healthcare Systems, readers will discover AI-based smart paradigms that enable reliable predictions of infectious disease dynamics, which can play a crucial role in preventing disease transmission. The book also delves into the application of extended reality in various healthcare contexts, summarizing the current research landscape. Additionally, it presents intelligent models for smart recommender systems that can assist in personal well-being services and computer-aided drug discovery and design methods.

Featuring contributions from experts in the field, this comprehensive reference book is designed for healthcare professionals, researchers, and students across multiple disciplines, including industrial engineering, systems engineering, biomedical engineering, computer science, electronics, and communications engineering. The case studies included highlight the business processes behind the use of big data and health analytics, showcasing how these technologies can significantly improve healthcare delivery and patient care.