Generative Intelligence in Healthcare: Transforming Patient Care with AI Creativity

Editors

Sakshi Gupta, Umesh Gupta, Moolchand Sharma, Kamal Malik (Editors)

ISBN: 9781032887425

Published: Paperback edition, 2026 (hardback first published April 2025)

Format: Paperback

Language: English

Publisher: CRC Press

Description

Generative Intelligence in Healthcare: Transforming Patient Care with AI Creativity explores the intersection of artificial intelligence and healthcare with a focus on generative intelligence. The book introduces the concept of generative intelligence and its transformative potential in patient care, showcasing applications that go beyond conventional AI approaches. It delves into the use of generative models for personalised medicine, data analytics, and predictive modelling, providing real-world examples of how AI creativity can revolutionise treatment strategies and diagnostic processes, including how generative AI can help healthcare providers automatically generate prescriptions, discharge summaries, and patient condition reports. The book's particular strength lies in its comprehensive examination of ethical considerations and regulatory frameworks, ensuring a responsible and transparent integration of generative intelligence in healthcare.

Key Features

Covers generative AI applications across drug discovery, medical imaging, and large language models in healthcare · Dedicated chapters on ethical considerations and regulatory frameworks for responsible AI adoption · Real-world case studies in cancer detection, Alzheimer's diagnosis, and personalised medicine · Addresses data privacy alongside precision treatment · Part of the Artificial Intelligence for Sustainable Engineering and Management book series

Coverage

Drug discovery and development with generative AI; generative models for image-to-image translation and medical imaging; large language models in healthcare information systems; AI in nanocarrier design and drug delivery for cancer diagnosis and therapy; predictive analytics for early cancer detection; deep learning for early detection of Alzheimer's disease; generative AI in personalised medicine and data privacy; natural language processing applications in healthcare; recent applications of AI in drug discovery.

About the Authors

Sakshi Gupta is an Assistant Professor at Manav Rachna International Institute of Research and Studies, Faridabad, Haryana, with a PhD from Birla Institute of Technology, Mesra. Her research interests include IoT, mobile ad-hoc networks, and machine learning.

Umesh Gupta is an Associate Professor at the School of Computer Science & Artificial Intelligence, Bennett University, Greater Noida, India, with a PhD in Machine Learning from the National Institute of Technology, Arunachal Pradesh.

Moolchand Sharma is an Assistant Professor in Computer Science and Engineering at Maharaja Agrasen Institute of Technology, GGSIPU Delhi, researching AI, nature-inspired computing, and cloud security.

Kamal Malik is a Professor in CSE at CTU Ludhiana, Punjab, India, with research spanning AI, machine learning, deep learning, and computational neurosciences.

Table of Contents

1. Drug Discovery and Development with Generative Artificial Intelligence
2. Generative Models for Image-to-Image Translation
3. Generative Models in Medical Imaging
4. Revolutionizing Healthcare: The Impact of Generative AI and Large Language Models
5. AI in Nanocarrier Design and Drug Delivery for Cancer Diagnostic and Therapy
6. Large Language Models in Healthcare Information Systems
7. Predictive Analytics for Early Cancer Detection
8. Revolutionizing Medicine: The Impact of Artificial Intelligence in Healthcare
9. Deep Learning Innovations in Healthcare: Early Detection of Alzheimer's Disease
10. Generative AI in Personalized Medicine: Enhancing Data Privacy and Precision Treatment
11. Transforming Healthcare through Generative AI
12. Machine Learning to Analyse Melodies and Pitches in Carnatic Music
13. Unlocking Healthcare's Potential with Natural Language Processing
14. Recent Applications of AI in Drug Discovery and Development

Why buy this book?

A comprehensive academic reference on generative AI in healthcare that balances technical depth with ethical and regulatory analysis. A valuable addition for medical, biomedical engineering, and computer science libraries supporting research on AI-driven diagnostics and patient care.

Keywords

generative AI, healthcare AI, medical imaging, drug discovery, large language models, personalised medicine, AI ethics healthcare, predictive analytics

Target Audience

Healthcare professionals, academics, graduate students and researchers in biomedical engineering, electrical engineering, and computer science

Genre

Generative AI in Healthcare

Q&A

Q: What is "Generative Intelligence in Healthcare" about?
A: It examines how generative AI models are transforming patient care, from personalised medicine and diagnostics to automatically generating prescriptions and discharge summaries.

Q: Does the book cover the ethics of generative AI in medicine?
A: Yes, it includes a comprehensive examination of ethical considerations and regulatory frameworks for responsible AI integration in healthcare.

Q: Who should read this book?
A: Graduate students, researchers, and professionals in biomedical engineering, healthcare, and computer science who want a rigorous overview of generative AI applications in medicine.

Q: What clinical applications does the book explore?
A: Drug discovery, medical imaging, cancer detection, Alzheimer's diagnosis, and personalised treatment planning using generative AI models.

Q: Where can I buy Generative Intelligence in Healthcare: Transforming Patient Care with AI Creativity?
A: You can purchase it directly from CLNZ Books, with worldwide delivery and institutional invoicing available.

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