Si Thu Aung – författare

This book provides a practical guide to federated deep learning for healthcare including fundamental concepts, framework, and the applications comprising domain adaptation, model distillation, and transfer learning. It covers concerns in model fairness, data bias, regulatory compliance, and ethical dilemmas. It investigates several privacy-preserving methods such as homomorphic encryption, secure multi-party computation, and differential privacy. It will enable readers to build and implement federated learning systems that safeguard private medical information.

Features:

This book is aimed at graduate students and researchers in federated learning, data science, AI/machine learning, and healthcare.

This book provides a practical guide to federated deep learning for healthcare including fundamental concepts, framework, and the applications comprising domain adaptation, model distillation, and transfer learning. It covers concerns in model fairness, data bias, regulatory compliance, and ethical dilemmas. It investigates several privacy-preserving methods such as homomorphic encryption, secure multi-party computation, and differential privacy. It will enable readers to build and implement federated learning systems that safeguard private medical information.

Features:

This book is aimed at graduate students and researchers in federated learning, data science, AI/machine learning, and healthcare.

This book is an in-depth exploration of brain networks, providing a comprehensive understanding of their structures, functions, and implications for personalization through artificial intelligence. Readers will gain insights into the intricate workings of the brain, making this book an indispensable resource for those seeking a thorough grasp of neuroscience concepts. It offers the seamless integration of neuroscience principles with artificial intelligence applications. The book bridges these two domains, elucidating how advancements in AI draw inspiration from the complexities of the human brain. This interdisciplinary approach sets the book apart, offering readers a holistic view of cutting-edge technologies. Readers can expect practical applications and real-world case studies that illustrate the tangible benefits of the concepts discussed. From personalized healthcare solutions to adaptive learning systems, the book goes beyond theory, empowering readers to apply knowledge in diverse domains. This practical emphasis enhances the book’s relevance for professionals and researchers alike. The inclusion of online enhancements, such as interactive visualizations, downloadable supplementary materials, and engaging video content, transforms the reading experience into an interactive learning journey. This added value distinguishes the book by providing readers with hands-on tools to deepen their understanding and apply newfound knowledge.

This book doesn’t just dwell on current technologies; it takes readers into the future by exploring emerging trends at the intersection of neuroscience and artificial intelligence. By delving into potential breakthroughs and innovations, the book equips readers with insights that are forward-thinking and relevant in an ever-evolving technological landscape.