Gaur / Abraham | Generative Artificial Intelligence and Ethics for Healthcare | Buch | 978-0-443-33124-4 | sack.de

Buch, Englisch, 225 Seiten, Format (B × H): 191 mm x 235 mm

Gaur / Abraham

Generative Artificial Intelligence and Ethics for Healthcare


Erscheinungsjahr 2025
ISBN: 978-0-443-33124-4
Verlag: Elsevier Science

Buch, Englisch, 225 Seiten, Format (B × H): 191 mm x 235 mm

ISBN: 978-0-443-33124-4
Verlag: Elsevier Science


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.

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Weitere Infos & Material


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


Gaur, Loveleen
Dr. Loveleen Gaur, PhD currently serves as an adjunct professor at Taylor University, Malaysia, and the University of South Pacific, Fiji, as well as an academic consultant with the Australian School of Graduate Studies. Prior to moving to the USA, she was a Professor at Amity University, India. She has supervised numerous PhD scholars and postgraduate students, primarily in Artificial Intelligence and Data Analytics applied to business and healthcare.

Under her leadership, the AI/Data Analytics research cluster has published extensively in high-impact journals and established strong global collaborations with leading experts. She is a Senior Member of IEEE, a Series Editor with CRC Press and Wiley, and was recently appointed Co-Editor of the journal Communications in Statistics: Case Studies, Data Analysis and Applications.

Dr. Gaur has a robust record of high-indexed publications (SCI/ABDC/WoS/Scopus), numerous patents and copyrights, and has edited or authored several books with top-tier publishers. Her areas of specialization include Artificial Intelligence, Machine Learning, Pattern Recognition, Internet of Things, Data Analytics, and Business Intelligence. She has been honored with several prestigious national and international awards.

Abraham, Ajith
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.



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