Smarter Healthcare through Generative Intelligence

1. Auflage 2026
ISBN: 978-1-032-96074-6
Verlag: Taylor & Francis Ltd

Buch, Englisch, 232 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 453 g

Reihe: Advances in Computational Collective Intelligence

Generative AI has potential to improve healthcare because it can enable smarter, more efficient solutions across diagnostics, treatment, and patient care. By analyzing vast amounts of medical data, generative AI systems can identify patterns, predict disease progression, and assist in early diagnosis with remarkable accuracy. It enhances personalized medicine by generating tailored treatment plans based on individual patient profiles, including genetic, lifestyle, and clinical data.

Smarter Healthcare through Generative Intelligence examines the convergence of healthcare and intelligent computation and how it is reshaping the global healthcare landscape. Focusing on applications and management issues, it looks at generative models, privacy-aware distributed computing, smart sensing technologies, and policy frameworks. From data augmentation to drug discovery and from mental health assessment to intelligent patient communication, the book explores the ways generative AI can transform healthcare.

Highlights include:

· Fog computing for smart healthcare

· Leveraging generative intelligence to overcome dataset limitations in emotional wellbeing analysis

· Ethical considerations in AI-driven smart healthcare

· Designing intelligent chatbots for healthcare

Generative AI is transforming healthcare into a more proactive, precise, and patient-centered industry. Written for healthcare practitioners, researchers, policymakers, and technologists, this book is a guide on how they can design, adopt, and govern generative technologies for smarter healthcare.

Zielgruppe

Professional Practice & Development and Professional Reference

Autoren/Hrsg.

Gupta, Aditya

Jain, Vibha

Singh, Amritpal

Verma, Prabal

Ayoub Shaikh, Tawseef

Inhaltsverzeichnis

1. Introduction to Generative Intelligence in Healthcare 2. Fog Computing for Smart Healthcare 3. Generative Adversarial Network (GAN) for Healthcare Data Augmentation and Bias Mitigation 4. MSQIGA: Multimodal Summarization with Quantum-Inspired Genetic Algorithm 5. Revolutionizing Healthcare: Designing Intelligent Chatbots with NLP 6. Futuristic Machine Learning Modeling Approach to Predict Communication Disorders: Stammering Based on Temperaments of Children 7. Smart Strategies in Mental Health: Leveraging Generative Intelligence to Overcome Dataset Limitations in Emotional Wellbeing Analysis 8. Leveraging Drug Synergism to Uncover Novel Drug Effects: A Literature Review 9. Evolution of Smart Health Technology for Neuropathic Foot Interventions 10. Ethical Considerations in AI-Driven Smart Healthcare: What Matters for Policy

Über Autor(innen)

Vibha Jain is working as an Assistant Professor in the Department of Computer Science and Engineering at Thapar Institute of Engineering and Technology, Patiala (Punjab), India since 2024. She completed her Ph.D. in Computer Science and Engineering from the Netaji Subhas University of Technology, Delhi. She is a Gold Medallist from the National Institute of Technology, Hamirpur for her Master of Technology in Computer Science and Engineering. She has more than 35 papers in her account and has an interest in vast research domains, including the Internet of Things, Blockchain, Edge/fog Computing, and Resource Scheduling/allocation.

Aditya Gupta has been serving as an Assistant Professor with the Department of Electrical and Instrumentation Engineering, Thapar Institute of Engineering and Technology, Patiala (Punjab), India since 2023. He received his doctoral degree in Computer Science and Engineering from Dr B R Ambedkar National Institute of Technology, Jalandhar for his dissertation on "Design and Analysis of a Centric Intelligent Frameworks for Healthcare 4.0”. His research interests include Healthcare Informatics, Predictive Analytics, and Cyber-Physical Systems. He has published various research papers in High-Impact reputed international journals and completed centrally funded research projects, jointly sponsored by the World Bank and the Ministry of Education (MoE), Government of India.

Amritpal Singh has been serving as Assistant Professor in the Department of Computer Science and Engineering, Dr B R Ambedkar National Institute of Technology Jalandhar, India. He has received his PhD degree in Computer Science and Engineering from Thapar University, Patiala, India. He served both industry and academia. He has published many articles in journals of high repute. His research interests include Probabilistic Data Structures, Machine Learning and Big Data.

Prabal Verma currently an Assistant Professor in the Department of Information Technology at NIT Srinagar, India, with prior academic roles under TEQIP-III and at Thapar Institute of Engineering and Technology, holds a Ph.D. in Computer Science and Engineering from Guru Nanak Dev University, Amritsar, and has research interests in Big Data Analytics, Machine/Deep Learning, and Edge–Cloud Computing; he has published extensively in high-impact international journals and conferences by IEEE, Elsevier, Wiley, Taylor \& Francis, and Springer, serves as a reviewer and editorial board member for reputed SCI-indexed journals, led TEQIP-III projects, is currently executing a JKSTIC-funded project, and holds GATE, UGC-NET, and JKSET qualifications with high percentiles.

Tawseef Ayoub Shaikh is Senior Assistant Professor at the Department of Computer Science & Engineering, National Institute of Technology (NIT) Srinagar, India. Before Joining NIT Srinagar, he worked as an Assistant Professor in the CSE Department at Pandit Deen Dayal Energy University (PDEU), Gandhinagar, Gujrat. Also, he worked as an Assistant Professor (TEQIP-III, NPIU, MHRD) at the Computer Science Engineering Department, Baba Ghulam Shah Badshah University (BGSBU) Rajouri, Jammu & Kashmir, for three years. He was awarded a Visvesvaraya Ph.D. fellowship from MeitY (Ministry of Electronics and Information Technology, Media Lab Asia, GoI), pursuing his Ph.D. He has been granted 6 fully funded projects from NPIU, MHRD, and JKSTIC, and all these projects have been completed. He has qualified UGC NET, GATE, and JKSLET in Computer Science Engineering/Applications. His research interests include Biomedical Data Analytics, Computer Aided Diagnostics Tools for Precision Medicine, Healthcare Informatics, Pattern Recognition, and Machine Intelligence. He has published various journal and conference papers, book chapters etc. in reputed International Publication houses and has authored 2 books.