Generative Intelligence in Healthcare

Transforming Patient Care with AI Creativity
1. Auflage 2025
ISBN: 978-1-032-88740-1
Verlag: Taylor & Francis Ltd (Sales)

Buch, Englisch, 398 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 730 g

Reihe: Artificial Intelligence for Sustainable Engineering and Management

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.

Zielgruppe

Postgraduate, Professional Reference, and Undergraduate Advanced

Autoren/Hrsg.

Gupta, Sakshi

Gupta, Umesh

Sharma, Moolchand

Malik, Kamal

Fachgebiete

• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizinische Fachgebiete Bildgebende Verfahren, Nuklearmedizin, Strahlentherapie Radiologie, Bildgebende Verfahren
• Technische Wissenschaften Sonstige Technologien | Angewandte Technik Medizintechnik, Biomedizintechnik
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizintechnik, Biomedizintechnik, Medizinische Werkstoffe

Inhaltsverzeichnis

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

Über Autor(innen)

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.