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Full Description
Generative artificial intelligence (AI) is a transformative force in smart healthcare. It can produce contents virtually indistinguishable from human-created material, with the power to redefine healthcare and revolutionize how medical science interacts with technology. This book presents the potential applications and benefits of generative AI in healthcare and discusses its execution challenges and ethical aspects.
Generative Artificial Intelligence in Healthcare: Current Practices and Future Development starts by reviewing the past and then discussing the present of generative AI-based systems and the potential challenges the future might bring. It then highlights the integration of generative AI with IoT and blockchain technologies along with offering case studies. The book explores how to integrate augmented and virtual reality into generative AI-based healthcare and covers the development of an effective machine algorithm for generative AI-based healthcare, as well as the design and implementation of generative adversarial networks (GANs) in healthcare systems.
Discussions about data security and ergonomic design for healthcare products are also included in the book. This book will provide a platform for the past, present, and future of generative AI and will help researchers and healthcare practitioners generate more robust solutions.
Contents
Chapter 1 Transformative Influence of Explainable AI in Smart Healthcare. Chapter 2 Disease Diagnosis and Clinical Research Using Generative AI. Chapter 3 Transformative Impact on Disease Diagnosis Using Generative AI. Chapter 4 Exploring Digital Tools Utilizing Generative AI in Healthcare. Chapter 5 Ethical Considerations in Generative Artificial Intelligence in Healthcare. Chapter 6 Navigating the Ethical Crossroads of Generative AI in Healthcare. Chapter 7 The Pinnacle of Disease Diagnosis through Generative Artificial Intelligence (AI): Transforming Healthcare. Chapter 8 Exploring Generative AI and IoMT in Diabetes Prediction. Chapter 9 Machine Learning Algorithms for Analyzing Medical Images and C.T. Scans. Chapter 10 Integrity in Innovation: Harnessing Generative AI for Next-Generation Healthcare. Chapter 11 Generative Adversarial Networks (GANs) for Healthcare Applications. Chapter 12 Innovations in Smart Healthcare: Integrating Generative Artificial Intelligence with Federated Learning. Chapter 13 Generative Artificial Intelligence in Healthcare: Approaches and Applications. Chapter 14 Generative AI in Healthcare: A European Case Study. Chapter 15 Opportunities, Challenges, and Future Directions of Generative Artificial Intelligence in Healthcare. Chapter 16 A Reassessment of Generative AI for Healthcare and Future Work Environments.
