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Elsevier

Generative Artificial Intelligence and Ethics for Healthcare

  • 1 Edición - 12 de septiembre de 2025
  • Última edición
  • Autores: Loveleen Gaur, Ajith Abraham
  • Idioma: Inglés

Generative Artificial Intelligence and Ethics for Healthcare conducts a deep dive into the potential issues and challenges associated with Generative AI applications. The book b… Leer más

Descripción

Generative Artificial Intelligence and Ethics for Healthcare conducts a deep dive into the potential issues and challenges associated with Generative AI applications. The book begins with foundational concepts of generative AI and then explores ethical theories, including specific case studies in healthcare, and concludes with discussions on policy and future implications. Written for healthcare professionals, policymakers, academics and AI developers, by authors who have a thorough understanding of AI and machine learning in the healthcare.

Puntos claves

  • Establishes a basic understanding of the concept of Generative AI, along with various ethical challenges
  • Focuses on specific issues such as Data Privacy, Patient Data Ownership, Trust, Accountability, and Informed Consent
  • Explores the latest concepts of Health Equity, Lawfulness, and Empathy in relation to Generative AI and the role of governability

De interès para

Healthcare professionals, Policymakers and regulators, AI developers and engineers, Academics and researchers and Students and educators

Índice

1. Generative AI in Healthcare: Introduction, Concept, Applications, and Challenges

2. Understanding Training Data and Mitigating Biases in Training Data

3. Calibrating Generative AI Models for Healthcare

4. Explainability in Generative AI and LLMs

5. Ethical Considerations in Generative AI Development and Usage

6. Ethical Concerns of Generative AI in Healthcare Applications

7. Ethical Concern of Data Privacy and Patient Data Ownership

8. Trust, Accountability, and Informed Consent: Cornerstones of Ethical Practice in Clinical Medicine

9. Personalized Medicine and Data Privacy: Where to Draw the Boundary?

10. Autonomous Medical Diagnosis: How to Balance Accuracy and Accountability?

11. Health Equity and Generative AI: Role, Impact, and Challenges

12. Lawfulness and Generative AI

13. Empathy and Generative AI: Role and Ethical Challenges

14. Role of Governability and Generative AI for Healthcare

Detalles del producto

  • Edición: 1
  • Última edición
  • Publicado: 12 de septiembre de 2025
  • Idioma: Inglés

Sobre los autores

LG

Loveleen Gaur

Dr. Loveleen Gaur is an internationally recognized academic leader, educator, and researcher in Artificial Intelligence, Generative AI, and Data Analytics. She serves as Director of the Symbiosis Artificial Intelligence Institute (SAII), Symbiosis International University, Pune, where she leads interdisciplinary education and ethical AI innovation.

With over two decades of experience, Dr. Gaur has held senior academic roles at institutions in India and abroad, including Amity University, and holds adjunct professorships at Taylor’s University (Malaysia) and the University of the South Pacific (Fiji). Her work spans curriculum design, doctoral supervision, research leadership, and global collaborations.

Named among the World’s Top 2% Scientists (Stanford/Elsevier, 2024), she has authored and edited numerous books and published extensively in high-impact journals. Her research focuses on AI in healthcare, explainable AI, sustainability, and business intelligence. A Senior IEEE member and journal editor, she is committed to advancing ethical, socially impactful AI.

Afiliaciones y experiencia
Adjunct Professor, The University of South Pacific, Suva, Fiji

AA

Ajith Abraham

Dr. Ajith Abraham is the Pro Vice-Chancellor for Academics, Research, Incubation, and International Relations at Bennette University. He is also the Founding Director of Machine Intelligence Research Labs (MIR Labs), a global non-profit scientific network that connects academia and industry to support research and innovation. He is also serving as Vice Chancellor of Sai University, Chennai. His research interests include artificial intelligence and machine intelligence, cyber-physical systems, the Internet of Things (IoT), network security, Web intelligence, sensor networks, and data mining. He serves as Chair of the IEEE Systems, Man, and Cybernetics Society Technical Committee on Soft Computing and has held editorial leadership roles, including Editor-in-Chief of Engineering Applications of Artificial Intelligence. Dr. Abraham earned his Ph.D. in Computer Science from Monash University, Australia.
Afiliaciones y experiencia
Sai University, Tamil Nadu, India

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