Generative Artificial Intelligence in Healthcare

Current Practices and Future Development
1. Auflage 2025
ISBN: 978-1-032-78484-7
Verlag: Taylor & Francis Ltd

Buch, Englisch, 352 Seiten, Format (B × H): 156 mm x 234 mm

Reihe: Artificial Intelligence in Smart Healthcare Systems

Generative artificial intelligence (AI) is a transformative force in smart healthcare. It can produce contents virtually indistinguishable from human-created material, with the power to redefine healthcare and revolutionize how medical science interacts with technology. This book presents the potential applications and benefits of generative AI in healthcare and discusses its execution challenges and ethical aspects.

Generative Artificial Intelligence in Healthcare: Current Practices and Future Development starts by reviewing the past and then discussing the present of generative AI–based systems and the potential challenges the future might bring. It then highlights the integration of generative AI with IoT and blockchain technologies along with offering case studies. The book explores how to integrate augmented and virtual reality into generative AI–based healthcare and covers the development of an effective machine algorithm for generative AI–based healthcare, as well as the design and implementation of generative adversarial networks (GANs) in healthcare systems.

Discussions about data security and ergonomic design for healthcare products are also included in the book. This book will provide a platform for the past, present, and future of generative AI and will help researchers and healthcare practitioners generate more robust solutions.

Zielgruppe

Professional Reference

Autoren/Hrsg.

Tek, Ong Eng

Kumar, Rajendra

Ramamoorthy, Shankar

Jain, Vishal

Kose, Utku

Fachgebiete

• Technische Wissenschaften Technik Allgemein Technische Zuverlässigkeit, Sicherheitstechnik
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken
• Technische Wissenschaften Technik Allgemein Industrial Engineering

Inhaltsverzeichnis

Chapter 1 Transformative Influence of Explainable AI in Smart Healthcare. Chapter 2 Disease Diagnosis and Clinical Research Using Generative AI. Chapter 3 Transformative Impact on Disease Diagnosis Using Generative AI. Chapter 4 Exploring Digital Tools Utilizing Generative AI in Healthcare. Chapter 5 Ethical Considerations in Generative Artificial Intelligence in Healthcare. Chapter 6 Navigating the Ethical Crossroads of Generative AI in Healthcare. Chapter 7 The Pinnacle of Disease Diagnosis through Generative Artificial Intelligence (AI): Transforming Healthcare. Chapter 8 Exploring Generative AI and IoMT in Diabetes Prediction. Chapter 9 Machine Learning Algorithms for Analyzing Medical Images and C.T. Scans. Chapter 10 Integrity in Innovation: Harnessing Generative AI for Next-Generation Healthcare. Chapter 11 Generative Adversarial Networks (GANs) for Healthcare Applications. Chapter 12 Innovations in Smart Healthcare: Integrating Generative Artificial Intelligence with Federated Learning. Chapter 13 Generative Artificial Intelligence in Healthcare: Approaches and Applications. Chapter 14 Generative AI in Healthcare: A European Case Study. Chapter 15 Opportunities, Challenges, and Future Directions of Generative Artificial Intelligence in Healthcare. Chapter 16 A Reassessment of Generative AI for Healthcare and Future Work Environments.

Über Autor(innen)

Dr. Rajendra Kumar is working as an Associate Professor at the Department of Computer Science & Engineering, School of Engineering & Technology, Sharda University. Dr. Kumar has 26 years of teaching and research. He is editor-in-chief of ADI Journal of Recent Innovations (AJRI), Indonesia, and also a reviewer of Medical & Biological Engineering & Computing (Springer Journal), and Expert Systems with Applications (a refereed international journal of Elsevier). He is a senior member of IEEE. He has chaired many sessions at international conferences and delivered keynote talks. He has published 05 textbooks, 08 edited books, 15 book chapters, 10 conference proceedings, 02 monographs, and 04 patents. https://www.sharda.ac.in/faculty/details/rajendrakumar

Dr. Shankar Ramamoorthy an IITian with 34 years of academic and industry experience is Professor of Computer science at Galgotias University, Greater Noida, India. Dr. Shankar Ramamoorthy has spent a larger part of corporate life in companies like C.DOT, Bharti Group, Alcatel, Amdocs, Harman, UST Global, Ness Technologies to name a few in senior executive roles and created digital transformation pack to make students industry ready per top emerging IT trends @ 2030 using top 30 technologies guided by Gartners Hype Cycle. He has been in senior academic leadership roles in CMRIT & Presidency University before joining Sharda University as Dean. https://www.sharda.ac.in/faculty/details/shankarramamoorthy/

Dr. Vishal Jain is presently working as a Professor in the department of Computer Science & Engineering at Sharda University, Greater Noida, U.P. He has more than 17 years of experience in the academics. He has authored more than 100 research papers in reputed conferences and journals, including Web of Science and Scopus. He has authored and edited more than 45 books with various reputed publishers, including Springer, Apple Academic Press, CRC, Taylor and Francis Group, Scrivener, Wiley, Emerald and IGI-Global. His research areas include information retrieval, semantic web, ontology engineering, data mining, ad hoc networks, and sensor networks. http://www.sharda.ac.in/faculty/details/dr-vishal-jain

Dr. Utku Kose received a B.S. degree in 2008 in computer education from Gazi University, Turkey as a faculty valedictorian. He received an M.S. degree in 2010 from Afyon Kocatepe University, Turkey in the field of computer and a D.S. / Ph. D. degree in 2017 from Selcuk University, Turkey in the field of computer engineering. Currently, he is an Associate Professor at Suleyman Demirel University, Turkey. Kose also gave lectures at other higher education institutions such as Gazi University and Istanbul Arel University. He also works as a Visiting Researcher at the University of North Dakota, USA. With more than 300 publications his research interests include artificial intelligence, machine ethics, artificial intelligence safety, biomedical applications, optimization, chaos theory, distance education, e-learning, computer education, and computer science. https://www.utkukose.com/

Dr. Eng-Tek Ong is a highly experienced and accomplished professor at UCSI University, Kuala Lumpur, Malaysia. He holds a PhD from Cambridge University, UK. He has been awarded the Fundamental Research Grant Scheme (FRGS) three times by the Ministry of Education for his research on science process skills and inquiry learning in science for teachers. UNESCO Bangkok has also awarded him twice to undertake research on HIV-AIDS Preventive Education. He was the Chief Reviewer for CoSMEd 2021 and is an editorial member for a few journals, including Learning Science and Mathematics (LSM) Online Journal and Journal of Science and Mathematics Education in Southeast Asia. https://www.ucsiuniversity.edu.my/professor-dr-ong-eng-tek