Transforming Healthcare (eBook, PDF)

Mode, Technologies, and Implementation
Redaktion: Jain, Ankush; Mosbah, Mohamed; Singal, Gaurav; Srivastava, Vishal

• Format: PDF

Produktbeschreibung

This comprehensive volume explores cutting-edge technologies, groundbreaking methodologies, and insightful ethical considerations. It brings together leading minds and research across diverse domains, offering readers a glimpse into the future of healthcare. From leveraging AI in diagnostics and personalized treatments to advancing telemedicine and remote patient monitoring, the text addresses real-world challenges and opportunities in the rapidly evolving healthcare industry.

Key features:

• Innovative approaches to early disease detection, including Alzheimer's and cancer, using machine learning and deep learning techniques.
• State-of-the-art applications of design thinking, meta-heuristics, and federated learning in healthcare.
• Ethical perspectives on the use of AI technologies and their impact on businesses and patient care.
• A deep dive into the role of IoT, NLP, and AI-driven image processing in revolutionizing healthcare delivery.
• Generalized models analyzing trade credits and their implications for healthcare supply chains.

Whether you're a researcher, healthcare professional, or technology enthusiast, this book serves as an invaluable resource for understanding and shaping the future of health technologies. Packed with diverse perspectives and actionable insights, it's a must-read for anyone passionate about making a difference in healthcare.

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Produktdetails

• Verlag: Taylor & Francis eBooks
• Seitenzahl: 282
• Erscheinungstermin: 28. Juli 2025
• Englisch
• ISBN-13: 9781040369050
• Artikelnr.: 74622673

Autorenporträt

Ankush Jain is an Assistant Professor in the Department of Computer Science and Engineering at Netaji Subhas University of Technology, Dwarka, New Delhi. He completed his M.Tech. and PhD from ABV-Indian Institute of Information Technology and Management (ABV-IIITM), Gwalior. Earlier, he worked as an Assistant Professor at Indira Gandhi Delhi Technical University for Women (IGDTUW), Delhi. Dr. Jain has published research articles, patents, and books in internationally acclaimed venues. He serves as a reviewer in various international journals, e.g., IEEE Transactions on Evolutionary Computation, IEEE Transactions on System, Man, and Cybernetics, IEEE Transactions on Computational Social Systems, IEEE Sensors Journal, Information Processing and Management, Expert Systems with Applications, Soft Computing, and JMLC. His research interests include Recommendation Systems, Evolutionary Computation, Computer Vision, Pattern Recognition, and Machine Learning. He is a Life Member of the ISTE and International Society of Engineers and a professional member of the IEEE and ACM. Vishal Srivastava is an Assistant Professor in the Department of Computer Science and Engineering, Motilal Nehru National Institute of Technology (MNNIT) Allahabad, Prayagraj, India. His main research interests are graphs, complex social networks, image-based computations in AI, pattern recognition, and evolutionary computing. He has published research articles, patents, and books in internationally acclaimed venues. Gaurav Singal received his M.Tech. and PhD from the CSE Department, Malaviya National Institute of Technology, Jaipur, India. He is an Assistant Professor with the CSE Department, at Netaji Subhas University of Technology, New Delhi, India. He has been actively working in research and teaching for the last Twelve years and published several reputed Conferences and Journals. His research interests include wireless Internet of Things, edge computing, Artificial intelligence, Deep learning, and software-defined networks. Dr Singal received a total research grant of approximately 55L from various agencies such as SERB, CST, and DBT on women's security, IoT Security, and Assistive devices. Mohamed Mosbah is a Professor of Computer Science at the Polytechnic Institute of Bordeaux (Bordeaux INP), France, where he currently serves as Vice-President. Previously, he held the position of Director of Industrial Partnerships and Innovation in Computer Science and Engineering. Prof. Mosbah conducts his research at LaBRI (Laboratoire Bordelais de Recherche en Informatique), a joint research center affiliated with the University of Bordeaux and CNRS, where he also served as Deputy Director. His research interests span distributed computing, security, sensor networks and their applications, and Intelligent Transportation Systems (ITS). In addition to his academic work, Prof. Mosbah is an active member of the scientific community, contributing to numerous technical program committees and organizing international conferences. He is also heavily involved in regional, national, and European research initiatives and projects. Currently, he leads an industrial chair dedicated to new mobilities and Intelligent Transportation Systems, in collaboration with the Bordeaux campus and a consortium of 10 partner companies. Prof. Mosbah's outstanding contributions have earned him recognition as a distinguished French scientific and academic figure, with his recent inclusion in the Who's Who in France 2025.

Inhaltsangabe

1. Innovating Health: Design Thinking in Emerging Technologies. 2. Next-Gen
Health Analytics: Meta-heuristic Bi-clustering of Gene Expression Data with
K-means. 3. Uncovering methods for early Alzheimer Diagnosis using Machine
Learning and Deep Learning. 5. A Comparative Study on Transfer Learning
Models and Ensemble Transfer Learning Models on Multi-Class Skin Cancer
Classification. 6. Benefits and Drawbacks of Using AI Technologies in
Healthcare Businesses: An Ethical Perspective. 8. Analysis and Predicting
Sector Data: The Role of Health News, Telemedicine, and Remote Patient
Monitoring. 9. A Generalized Model on the Effect of Trade Credits on
Healthcare Items under Multivariate Demand Based Production with Time
Dependent Deterioration and Partial Backlogging. 10. AI and NLP based
system for Early Detection of Malignant Cells of Brain through Image
Processing paving way for Personalized Treatment Strategies. 11. Advancing
Healthcare AI with Federated Learning. 12. A Systematic Review of
Applications, Challenges, Data Collection, and Academic Research in
Healthcare Using IoT. 13. Revolutionizing Healthcare: Cutting-Edge
Technologies and their Applications. 14. Speech Emotion Recognition in
Mental Health: A Novel Approach Using Machine Learning.