Responsible AI in Healthcare: Navigating the EU AI Act and Global Regulatory Frameworks examines how health systems design, deploy, and oversee AI under evolving legal and ethical mandates. It provides an integrated, practice-oriented roadmap for compliance and responsible innovation. This book offers the first integrated, comparative treatment of the EU AI Act and global regulatory frameworks for healthcare, translating ethics and law into operational evaluation, governance, and value assessment. Through structured cases, decision tools, and stakeholder methods, it equips researchers and clinicians to design, validate, and deploy AI responsibly-and to keep learning as regulations evolve. Readers gain actionable tools, checklists, and frameworks to operationalize ethical AI, prepare for audits and certifications, and anticipate global convergence (“Brussels Effect”) shaping digital health. The volume serves clinicians, administrators, developers, policy and legal experts seeking rigorous yet accessible guidance.Maps global health-AI regulation (EU AI Act, GDPR, HIPAA, WHO) into clear organizational requirements and governance modelsDemonstrates compliance in practice through hospital and public-health case studies, checklists, and implementation guidanceOperationalizes ethics-to-action via explainability, bias mitigation, and privacy-preserving methods (e.g., federated learning, differential privacy)Demonstrates compliance in practice through hospital and public-health case studies, checklists, and implementation guidance

Responsible AI in Healthcare: Navigating the EU AI Act and Global Regulatory Frameworks examines how health systems design, deploy, and oversee AI under evolving legal and ethical mandates. It provides an integrated, practice-oriented roadmap for compliance and responsible innovation. This book offers the first integrated, comparative treatment of the EU AI Act and global regulatory frameworks for healthcare, translating ethics and law into operational evaluation, governance, and value assessment. Through structured cases, decision tools, and stakeholder methods, it equips researchers and clinicians to design, validate, and deploy AI responsibly-and to keep learning as regulations evolve. Readers gain actionable tools, checklists, and frameworks to operationalize ethical AI, prepare for audits and certifications, and anticipate global convergence (“Brussels Effect”) shaping digital health. The volume serves clinicians, administrators, developers, policy and legal experts seeking rigorous yet accessible guidance.Maps global health-AI regulation (EU AI Act, GDPR, HIPAA, WHO) into clear organizational requirements and governance modelsDemonstrates compliance in practice through hospital and public-health case studies, checklists, and implementation guidanceOperationalizes ethics-to-action via explainability, bias mitigation, and privacy-preserving methods (e.g., federated learning, differential privacy)Demonstrates compliance in practice through hospital and public-health case studies, checklists, and implementation guidance