Generative Artificial Intelligence and Ethics for Healthcare

Bold, timely, and essential for healthcare professionals navigating the AI revolution, Generative Artificial Intelligence and Ethics for Healthcare by Loveleen Gaur and Ajith Abraham offers a practical, deeply informed guide to deploying generative AI responsibly across clinical settings worldwide.

From the first page, readers are drawn into clear explanations of generative AI technologies—large language models, image synthesis, and predictive systems—and their real-world applications in hospitals, clinics, telemedicine, and public health systems across the United States, Europe, India, and beyond. The authors translate complex concepts into actionable frameworks that address patient privacy, data governance, bias mitigation, explainability, and accountability.

This book balances rigorous ethical theory with concrete tools: case studies, policy analysis, risk-assessment strategies, and design principles tailored for clinicians, health informaticians, AI developers, regulators, and healthcare leaders. It highlights how to integrate AI into clinical decision-making while safeguarding equity, consent, and safety—essential reading for anyone responsible for AI adoption or regulation in healthcare environments.

Readers will gain immediate value: practical checklists for institutional review boards, guidance on compliance with international data protection standards, and step-by-step approaches to model validation and transparent reporting. The tone is professional yet accessible, making it suitable for academic courses, professional development, and hospital procurement teams.

For a future-ready perspective on AI ethics in health—rooted in real-world policy and technological insight—add Generative Artificial Intelligence and Ethics for Healthcare to your collection and equip your organization to innovate responsibly.

Note: eBooks do not include supplementary materials such as CDs, access codes, etc.