Generative Artificial Intelligence and Ethics for Healthcare
- 1st Edition - September 1, 2025
- Imprint: Academic Press
- Authors: Loveleen Gaur, Ajith Abraham
- Language: English
- Paperback ISBN:9 7 8 - 0 - 4 4 3 - 3 3 1 2 4 - 4
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 3 3 1 2 5 - 1
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… Read more
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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.
- 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
Healthcare professionals, Policymakers and regulators, AI developers and engineers, Academics and researchers and Students and educators
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
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
- Edition: 1
- Published: September 1, 2025
- Imprint: Academic Press
- Language: English
LG
Loveleen Gaur
Dr. Loveleen Gaur is an internationally renowned academic leader, educator, and researcher in the fields of Artificial Intelligence, Generative AI, and Data Analytics. She currently serves as the Director of the Symbiosis Artificial Intelligence Institute (SAII), Symbiosis International University, Pune, where she is spearheading interdisciplinary education and ethical innovation in AI.
With over two decades of academic experience, Dr. Gaur has held senior faculty positions at premier institutions in India and abroad. She served as Professor at Amity University and continues to hold honorary adjunct professorships at Taylor’s University (Malaysia) and the University of the South Pacific (Fiji). Her global academic engagements span curriculum design, PhD supervision, research leadership, and strategic international collaborations.
In 2024, she was recognized among the World’s Top 2% Scientists by Stanford University and Elsevier for her impactful scholarly contributions. She has authored and edited numerous research books with leading international publishers including Elsevier, Springer, Taylor & Francis, IGI Global, De Gruyter, and River Publishers, and has published extensively in high-impact journals indexed in SCI, Scopus, Web of Science, and ABDC. Her research spans domains such as AI in healthcare, neurodegenerative disease prediction, generative and explainable AI, sustainability, and business intelligence.
Dr. Gaur is also Co-Editor of the SCOPUS-indexed Taylor & Francis journal Communications in Statistics – Case Studies, Data Analysis and Applications. She holds multiple editorial roles—Guest Editor, Review Editor, and Topic Editor—for top-tier journals by Springer, MDPI, Frontiers, and others. As a Senior Member of IEEE, she actively contributes to the AI community through thought leadership, international speaking engagements, and advocacy for ethical, inclusive AI practices.
Her teaching portfolio includes undergraduate to doctoral courses on Generative AI, Deep Learning, Large Language Models (LLMs), Predictive Analytics, Business Intelligence, Power BI, and Explainable AI. Dr. Gaur is also certified in Agentic AI, AI for Business, and Generative AI Applications through globally recognized programs from IBM, Vanderbilt University, IIT Madras, and the University of Pennsylvania.
At SAII, Dr. Gaur is dedicated to shaping the next generation of AI professionals who are not only technically adept but also ethically grounded—bridging AI with societal impact across domains like healthcare, agriculture, education, and industry.
Affiliations and expertise
Professor and Director at the Symbiosis Artificial Intelligence Institute (SAII), Symbiosis International (Deemed University), Pune, IndiaAA
Ajith Abraham
Dr. Ajith Abraham is the Vice Chancellor at Sai University, Chennai. Before joining Sai University, he held the position of vice chancellor at prominent institutions and was also the founding director of Machine Intelligence Research Labs (MIR Labs), a non-profit scientific network for innovation and research excellence with headquarters in Seattle, USA. Dr. Abraham has completed research projects valued at over $110 million as an investigator or co-investigator from the United States, the European Union, Italy, the Czech Republic, France, Malaysia, China, and Australia. He has worked in a multidisciplinary setting for more than 35 years and has authored or co-authored more than 1,500+ research publications in artificial intelligence and related applications in the industry. A handful of his publications have been translated into Chinese and Russian, and one of his books has been translated into Japanese. The Scopus database has approximately 1,400 papers indexed, whereas the Thomson Web of Science has over 1,000 publications indexed.
In addition to other esteemed universities, Dr. Abraham has worked with researchers from MIT (USA), the University of Cambridge (UK), Harvard University (USA), and Oxford University (UK). According to Google Scholar, Dr. Abraham possesses over 63,000 scholarly citations with an H-index of over 118. He has delivered over 250 conference plenary talks and tutorials in more than 20 countries. From 2008 to 2021, Dr. Abraham chaired the IEEE Systems, Man, and Cybernetics Society Technical Committee on Soft Computing, which had more than 200 members. From 2011 to 2013, he represented Europe as a Distinguished Lecturer for the IEEE Computer Society (USA). Dr. Abraham is continuously listed in the Stanford/Elsevier list, highlighting the top 2% of the most cited scientists across the globe. Based on 2024 data, ScholarGPS listed Dr. Abraham as one of the world’s top 0.01% cited scientists in the engineering and computer science fields.
From 2016 to 2021, Dr. Abraham worked as the chief editor of Engineering Applications of Artificial Intelligence (EAAI) at Elsevier, New York. EAAI is one of the oldest journals (founded in 1988) in the artificial intelligencedomain. Additionally, he sat on the editorial boards of more than 15 international journals indexed by Thomson ISI. Dr. Abraham received his Ph.D. degree in artificial intelligence from Monash University, Melbourne, Australia (2001), a Master of Science degree from Nanyang Technological University, Singapore (1998), and a B.Tech (Hons) degree from the University of Calicut in 1990.
Affiliations and expertise
Vice-Chancellor, Sai University, Chennai, Tamil Nadu, India