Generative Intelligence in Healthcare (eBook, PDF)

Transforming Patient Care with AI Creativity
Redaktion: Gupta, Sakshi; Malik, Kamal; Sharma, Moolchand; Gupta, Umesh

• Format: PDF

Produktbeschreibung

This book explores the intersection of artificial intelligence and healthcare with a focus on generative intelligence. The book will introduce the concept of generative intelligence and its transformative potential in patient care, showcasing applications that go beyond conventional AI approaches.

Generative Intelligence in Healthcare: Transforming Patient Care with AI Creativity delves into the use of generative models for personalized medicine, data analytics, and predictive modelling, providing real-world examples of how AI creativity can revolutionize treatment strategies and diagnostic processes. It focuses on the origin and basics of generative AI, generative AI models, and possible areas in healthcare where generative AI can work. It discusses how generative AI model will help healthcare providers automatically generate prescriptions, discharge summaries, and patient conditions. The unique strength of this book lies in its comprehensive examination of ethical considerations and regulatory frameworks, ensuring a responsible and transparent integration of generative intelligence in healthcare. By addressing current challenges and envisioning future directions, this book serves as a valuable resource for healthcare professionals, researchers, and policymakers seeking to harness the full potential of AI creativity to enhance patient outcomes.

The book is written for graduate students, researchers, and professionals in biomedical engineering, electrical engineering, signal process engineering, biomedical imaging, and computer science.

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Produktdetails

• Verlag: Taylor & Francis eBooks
• Seitenzahl: 398
• Erscheinungstermin: 10. April 2025
• Englisch
• ISBN-13: 9781040329740
• Artikelnr.: 73653883

Autorenporträt

Sakshi Gupta is presently working as an Assistant Professor at Manav Rachna International Institute of Research and Studies, Faridabad. Haryana. She received her Ph.D. degree from the Birla Institute of Technology Mesra, Ranchi, and MCA from Gautam Buddha Technical University Lucknow, Uttar Pradesh. Her areas of interest include the Internet of Things, mobile ad-hoc networks, Body Area Networks, Machine learning, and Deep learning. She also has three published patents. Umesh Gupta is currently an Associate Professor at the School of Computer Science & Artificial Intelligence at Bennett University, Greater Noida, India. He received hi Ph.D. in Machine Learning from the National Institute of Technology, Arunachal Pradesh, India. He was awarded a gold medal for his Master's of Engineering (M.E.) from the National Institute of Technical Teachers Training and Research (NITTTR), Chandigarh, India, and Bachelor of Technology (B.Tech.) from Dr APJ, Abdul Kalam Technical University, Lucknow, India. He has more than 14 years of work experience in Academics and Research. His research interests include SVM, ELM, RVFL, machine learning, and deep learning approaches. He published three patents in the years 2021-2023. Moolchand Sharma is currently an Assistant Professor in the Department of Computer Science and Engineering at the Maharaja Agrasen Institute of Technology, GGSIPU Delhi. His research areas include Artificial Intelligence, Nature-Inspired Computing, Security in Cloud Computing, Machine Learning, and Search Engine Optimization. He is currently a doctoral researcher at DCR University of Science and Technology, Haryana. Kamal Malik is currently a Professor in CSE in School of Engineering and Technology at CTU Ludhiana, Punjab, India. Her major areas of research are Artificial Intelligence, Machine Learning, Deep Learning, Data Analytics, Computational Neurosciences and bio-inspired computing. She has more than 13 years of academic and research experience. Her passion is to teach computer science engineering and to encourage critical thinking for her students in domains like Machine Learning, Data Science, Business Analytics, Cloud Computing, Internet of Things and Blockchain.

Inhaltsangabe

Chapter 1- Drug Discovery and Development with Generative Artificial
Intelligence
Chapter 2- Generative Models for Image-to-Image Translation: Theoretical
Insights, Methodological Frameworks, and Practical Applications
Chapter 3- Generative Models in Medical Imaging
Chapter 4- Revolutionizing Healthcare: The Impact of Generative AI and
Large Language Models
Chapter 5- Artificial Intelligence in nanocarrier design and drug
deliveries via nanorobotics based personalized medicine for cancer
diagnostic and therapy
Chapter 6- Large Language Models in Healthcare Information Systems:
Overcoming Challenges to Achieve Personalized Care
Chapter 7- Predictive Analytics for Early Cancer Detection using Machine
Learning and Generative AI
Chapter 8- Revolutionizing Medicine: The Impact of Artificial Intelligence
in Healthcare
Chapter 9- Deep Learning Innovations in Healthcare: Early Detection of
Alzheimer's Disease
Chapter 10- Generative AI in Personalized Medicine: Enhancing Data Privacy
and Precision Treatment
Chapter 11- Transforming Healthcare through Generative AI
Chapter 12- Balancing Tradition and Technology Using Machine Learning to
Analyse Melodies and Pitches in Carnatic Music
Chapter 13- Unlocking Healthcare's Potential with Natural Language
Processing
Chapter 14- Recent applications of artificial intelligence in the process
of drug discovery and development