Machine Learning and Generative AI in Smart Healthcare

The healthcare landscape is constantly evolving, and one of the most significant concerns that healthcare professionals deal with is understanding how to use biomedical intelligence to improve patient outcomes. With the increasing complexity of healthcare computing systems, including technologies like deep learning and the Internet of Things, it can be challenging to navigate these advancements.

Machine Learning and Generative AI in Smart Healthcare is a practical tool for healthcare professionals, researchers, and policymakers who are seeking to implement biomedical intelligence solutions. It provides a clear roadmap for using prescriptive and predictive analytics in machine learning to enhance healthcare outcomes. Going beyond the basics, it delves into healthcare computing and networking complexities. By delving into topics such as data mining, disease prediction, and AI applications, deep learning approaches, decision support systems, and optimization techniques, this book equips readers with the practical knowledge they need to optimize healthcare delivery and management.

The many academic areas covered in this publication include, but are not limited to:

• Applications of AI Techniques in Healthcare
• Applications of AI Techniques in Wellbeing Systems
• Biomedical Applications of Machine Learning
• Biomedical Text Mining
• Data Mining in Healthcare
• Decision Support Systems for Healthcare
• Deep Learning and Methods to Explain Disease Prediction
• Disease Prediction Methods and Techniques
• Healthcare Information Systems
• Intelligent Computing and Platforms in Medicine
• Knowledge Discovery in Healthcare
• Machine and Deep Learning Approaches for Disease Data
• Machine and Deep Learning Approaches for Individual Health Data
• Machine Learning-Based Medical Systems
• Medical Data and Knowledge Bases
• Medical Expert Systems
• Medical Signal and Image Processing and Techniques
• Neural Networks in Medical Applications