{"product_id":"generative-ai-healthcare-ethics","title":"Generative Artificial Intelligence and Ethics for Healthcare","description":"\u003ch3\u003e\u003cb\u003eAuthors:\u003c\/b\u003e\u003c\/h3\u003e\n\u003cp\u003eLoveleen Gaur, Ajith Abraham\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cb\u003eISBN:\u003c\/b\u003e 9780443331244\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003ePublished:\u003c\/b\u003e September 12, 2025\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eFormat:\u003c\/b\u003e Paperback\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eLanguage:\u003c\/b\u003e English\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003ePublisher:\u003c\/b\u003e Academic Press (Elsevier)\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch2\u003e\u003cstrong\u003eDescription:\u003c\/strong\u003e\u003c\/h2\u003e\n\u003cp\u003e\u003cb\u003eGenerative Artificial Intelligence and Ethics for Healthcare\u003c\/b\u003e explores how generative AI is transforming clinical practice, research, and health systems, and what it means to use these technologies responsibly. The book starts with core concepts and architectures of generative AI and large language models, then examines ethical theories, case studies in healthcare, and the policy and governance questions that follow from real-world deployment. It closes with forward-looking chapters on lawfulness, empathy, health equity, and governability in AI-enabled healthcare ecosystems.\u003c\/p\u003e\n\u003cp\u003eWritten by leading experts in AI and machine learning, the book is designed to help healthcare professionals, policymakers, academics, and AI developers understand both the opportunities and the risks of generative AI in health, from bias and data privacy to transparency, accountability, and patient trust.\u003c\/p\u003e\n\u003ch2\u003e\u003cstrong\u003eKey Features:\u003c\/strong\u003e\u003c\/h2\u003e\n\u003cul\u003e\n\u003cli\u003eProvides a clear, accessible introduction to generative AI concepts, architectures, and applications in healthcare.\u003c\/li\u003e\n\u003cli\u003eExamines ethical challenges including bias in training data, explainability, trust, accountability, and informed consent. :contentReference[oaicite:1]{index=1}\u003c\/li\u003e\n\u003cli\u003eCovers critical topics such as data privacy, patient data ownership, health equity, and lawfulness in AI deployment.\u003c\/li\u003e\n\u003cli\u003eIncludes dedicated chapters on autonomous diagnosis, personalized medicine, empathy in AI systems, and the role of governability.\u003c\/li\u003e\n\u003cli\u003eConnects ethical analysis with policy debates and regulatory trends, helping readers anticipate emerging governance frameworks.\u003c\/li\u003e\n\u003cli\u003eOffers practical insights for clinicians, AI teams, and institutions that are evaluating or implementing generative AI tools.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch2\u003e\u003cstrong\u003eReadership:\u003c\/strong\u003e\u003c\/h2\u003e\n\u003cp\u003eHealthcare professionals; policymakers and regulators; AI developers and engineers; academics and researchers; students and educators interested in AI ethics, digital health, and health policy. \u003c\/p\u003e\n\u003ch2\u003e\u003cstrong\u003eAbout the Authors:\u003c\/strong\u003e\u003c\/h2\u003e\n\u003cp\u003e\u003cb\u003eLoveleen Gaur\u003c\/b\u003e is Professor and Director at the Symbiosis Artificial Intelligence Institute (SAII), Symbiosis International University, Pune. An internationally recognised researcher in generative and explainable AI, AI in healthcare, and data analytics, she has authored and edited numerous books and high-impact journal articles and was listed among the world’s top 2% scientists by Stanford University and Elsevier. \u003c\/p\u003e\n\u003cp\u003e\u003cb\u003eAjith Abraham\u003c\/b\u003e is Vice-Chancellor at Sai University, Chennai, and former founding director of Machine Intelligence Research Labs (MIR Labs). With 35+ years of multidisciplinary research, more than 1,500 publications, and over 60,000 citations, he is consistently ranked among the most cited AI scientists worldwide and has led major research projects across the US, EU, and Asia. \u003c\/p\u003e\n\u003ch2\u003e\u003cstrong\u003eTable of Contents:\u003c\/strong\u003e\u003c\/h2\u003e\n\u003col\u003e\n\u003cli\u003eGenerative AI in Healthcare: Introduction, Concept, Applications, and Challenges\u003c\/li\u003e\n\u003cli\u003eUnderstanding Training Data and Mitigating Biases in Training Data\u003c\/li\u003e\n\u003cli\u003eCalibrating Generative AI Models for Healthcare\u003c\/li\u003e\n\u003cli\u003eExplainability in Generative AI and LLMs\u003c\/li\u003e\n\u003cli\u003eEthical Considerations in Generative AI Development and Usage\u003c\/li\u003e\n\u003cli\u003eEthical Concerns of Generative AI in Healthcare Applications\u003c\/li\u003e\n\u003cli\u003eEthical Concern of Data Privacy and Patient Data Ownership\u003c\/li\u003e\n\u003cli\u003eTrust, Accountability, and Informed Consent: Cornerstones of Ethical Practice in Clinical Medicine\u003c\/li\u003e\n\u003cli\u003ePersonalized Medicine and Data Privacy: Where to Draw the Boundary?\u003c\/li\u003e\n\u003cli\u003eAutonomous Medical Diagnosis: How to Balance Accuracy and Accountability?\u003c\/li\u003e\n\u003cli\u003eHealth Equity and Generative AI: Role, Impact, and Challenges\u003c\/li\u003e\n\u003cli\u003eLawfulness and Generative AI\u003c\/li\u003e\n\u003cli\u003eEmpathy and Generative AI: Role and Ethical Challenges\u003c\/li\u003e\n\u003cli\u003eRole of Governability and Generative AI for Healthcare\u003c\/li\u003e\n\u003c\/ol\u003e\n\u003ch2\u003e\u003cstrong\u003eWhy buy this book?\u003c\/strong\u003e\u003c\/h2\u003e\n\u003cul\u003e\n\u003cli\u003eIt offers a single, structured reference that connects technical aspects of generative AI with concrete ethical and legal questions in healthcare.\u003c\/li\u003e\n\u003cli\u003eIt helps hospitals, regulators, and AI teams anticipate risks—bias, privacy breaches, opaque decisions—and design responsible governance frameworks.\u003c\/li\u003e\n\u003cli\u003eIt supports clinicians and health leaders who must evaluate AI tools, align them with professional standards, and maintain patient trust.\u003c\/li\u003e\n\u003cli\u003eIt is ideal for teaching and training, providing a complete overview of concepts, case studies, and policy discussions around AI ethics in health.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch2\u003e\u003cstrong\u003eKeywords:\u003c\/strong\u003e\u003c\/h2\u003e\n\u003cp\u003eGenerative AI, Healthcare ethics, Artificial intelligence in health, Data privacy, Patient data ownership, Health equity, Explainability, Accountability, Lawfulness, Empathy, AI governance, Trustworthy AI\u003c\/p\u003e\n\u003ch2\u003e\u003cstrong\u003eTarget Audience:\u003c\/strong\u003e\u003c\/h2\u003e\n\u003cp\u003eClinicians, Hospital and health system leaders, Policy makers, Health regulators, AI developers, Data scientists, Bioethicists, Health informatics specialists, Academic researchers, Graduate students in AI and health\u003c\/p\u003e\n\u003ch2\u003eGenre:\u003c\/h2\u003e\n\u003cp\u003e\u003cspan style=\"font-size: 0.875rem;\"\u003eHealthcare, Artificial intelligence, Ethics, Medical ethics and professional conduct, Health policy, Technology and society\u003c\/span\u003e\u003c\/p\u003e\n\u003ch3\u003e\u003cb\u003e📘 Learn more about shipping, delivery times, and returns, see our \u003ca href=\"https:\/\/clnzbooks.com\/pages\/faq-frequently-asked-questions\" style=\"color: #8b0000;\"\u003eFAQ here\u003c\/a\u003e.\u003c\/b\u003e\u003c\/h3\u003e","brand":"Academic Press","offers":[{"title":"Default Title","offer_id":43103557386314,"sku":null,"price":290.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0287\/7351\/5338\/files\/Generative.jpg?v=1764078449","url":"https:\/\/clnzbooks.com\/products\/generative-ai-healthcare-ethics","provider":"CLNZ Books ","version":"1.0","type":"link"}