Generative artificial intelligence and ethics for healthcare by Loveleen Gaur, Ajith Abraham.

By:

Gaur, Loveleen [author]

Contributor(s):

Abraham, Ajith, 1968- [author]

Material type:

text

Media type:

unmediated

Carrier type:

volume

ISBN:

9780443331244

Subject(s):

DDC classification:

23 610.28563

Contents:

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

Summary: 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.

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Holdings
Cover image	Item type	Current library	Home library	Collection	Shelving location	Call number	Materials specified	Vol info	URL	Copy number	Status	Notes	Date due	Barcode	Item holds	Item hold queue priority	Course reserves
	Gifted Books	Sai University Library General stacks		Reference		610.28563 ABR (Browse shelf(Opens below))					Available			G003091

Includes bibliographical references and index.

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

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.

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