Rejwan Bin Sulaiman – författare

Securing Health: The Convergence of AI and Cybersecurity in Healthcare explores how emerging technologies are revolutionizing modern medicine, ensuring not just innovation but safety and trust in the digital age. As artificial intelligence and cybersecurity rapidly transform industries, this timely book offers an in-depth look at their powerful convergence within the healthcare sector.Organized into four comprehensive parts, the book unveils cutting-edge strategies and practical applications shaping the future of medicine. From blockchain integration and smart wearables to adversarial machine learning and federated learning, each chapter offers critical insights into securing sensitive data, enhancing diagnostic accuracy, and preserving patient privacy.Discover how blockchain is being used to protect medical records and power real-time health monitoring for athletes, with a special focus on deployments in regions like Kurdistan. Learn how AI-driven tools are predicting complex diseases like cerebral palsy and post-transplant diabetes, offering hope for earlier intervention and better outcomes. Dive into the world of deep learning as it redefines medical imaging, from detecting COVID-19 via X-rays to advancing brain MRI segmentation.With contributions grounded in global case studies and research, Securing Health addresses the ethical, technical, and regulatory challenges of modern healthcare technology. Whether you’re a medical professional, tech innovator, or policy maker, this book equips you with the knowledge to navigate and lead in an era where AI and cybersecurity aren’t just enhancements—they’re essentials.Empowering, forward-thinking, and solution-focused, Securing Health is your essential guide to the future of secure, intelligent healthcare.

Securing Health: The Convergence of AI and Cybersecurity in Healthcare explores how emerging technologies are revolutionizing modern medicine, ensuring not just innovation but safety and trust in the digital age. As artificial intelligence and cybersecurity rapidly transform industries, this timely book offers an in-depth look at their powerful convergence within the healthcare sector.Organized into four comprehensive parts, the book unveils cutting-edge strategies and practical applications shaping the future of medicine. From blockchain integration and smart wearables to adversarial machine learning and federated learning, each chapter offers critical insights into securing sensitive data, enhancing diagnostic accuracy, and preserving patient privacy.Discover how blockchain is being used to protect medical records and power real-time health monitoring for athletes, with a special focus on deployments in regions like Kurdistan. Learn how AI-driven tools are predicting complex diseases like cerebral palsy and post-transplant diabetes, offering hope for earlier intervention and better outcomes. Dive into the world of deep learning as it redefines medical imaging, from detecting COVID-19 via X-rays to advancing brain MRI segmentation.With contributions grounded in global case studies and research, Securing Health addresses the ethical, technical, and regulatory challenges of modern healthcare technology. Whether you're a medical professional, tech innovator, or policy maker, this book equips you with the knowledge to navigate and lead in an era where AI and cybersecurity aren't just enhancements-they're essentials.Empowering, forward-thinking, and solution-focused, Securing Health is your essential guide to the future of secure, intelligent healthcare.

Securing Health: The Convergence of AI and Cybersecurity in Healthcare explores how emerging technologies are revolutionizing modern medicine, ensuring not just innovation but safety and trust in the digital age. As artificial intelligence and cybersecurity rapidly transform industries, this timely book offers an in-depth look at their powerful convergence within the healthcare sector.Organized into four comprehensive parts, the book unveils cutting-edge strategies and practical applications shaping the future of medicine. From blockchain integration and smart wearables to adversarial machine learning and federated learning, each chapter offers critical insights into securing sensitive data, enhancing diagnostic accuracy, and preserving patient privacy.Discover how blockchain is being used to protect medical records and power real-time health monitoring for athletes, with a special focus on deployments in regions like Kurdistan. Learn how AI-driven tools are predicting complex diseases like cerebral palsy and post-transplant diabetes, offering hope for earlier intervention and better outcomes. Dive into the world of deep learning as it redefines medical imaging, from detecting COVID-19 via X-rays to advancing brain MRI segmentation.With contributions grounded in global case studies and research, Securing Health addresses the ethical, technical, and regulatory challenges of modern healthcare technology. Whether you're a medical professional, tech innovator, or policy maker, this book equips you with the knowledge to navigate and lead in an era where AI and cybersecurity aren't just enhancements-they're essentials.Empowering, forward-thinking, and solution-focused, Securing Health is your essential guide to the future of secure, intelligent healthcare.

Federated Learning in Finance: Unlocking Privacy-Preserving and Cyber Resilience using AI is an edited volume designed to explore how Federated Intelligence can help the finance industry defend against cyber threats, detect fraud, and comply with regulations, all while keeping sensitive financial data secure and distributed.This book provides a comprehensive roadmap for integrating federated learning (FL) and artificial intelligence (AI)-driven cyber security into financial ecosystems. Unlike conventional AI systems that require data centralization, Federated Intelligence enables financial institutions to collaborate securely, train powerful AI models, and combat cyber threats.

Federated Learning in Finance: Unlocking Privacy-Preserving and Cyber Resilience using AI is an edited volume designed to explore how Federated Intelligence can help the finance industry defend against cyber threats, detect fraud, and comply with regulations, all while keeping sensitive financial data secure and distributed.This book provides a comprehensive roadmap for integrating federated learning (FL) and artificial intelligence (AI)-driven cyber security into financial ecosystems. Unlike conventional AI systems that require data centralization, Federated Intelligence enables financial institutions to collaborate securely, train powerful AI models, and combat cyber threats.