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Transforming Global Healthcare: The Role of AI and IoT in Modern Medical Systems explores the transformative potential of the integration of technologies such as AI, Big Data, IoT, and Blockchain in the healthcare sector. This comprehensive volume aims to illustrate how these advanced technologies can address sustainability challenges, improve decision-making processes, and enhance overall healthcare delivery. By mapping existing knowledge and forecasting future trends, the book provides a detailed roadmap for sustainable healthcare development. Key features include: - Explores AI, big data, IoT, and blockchain in healthcare in-depth. - Provides actionable strategies for energy management, waste disposal, and green supply chains - Provides in-depth coverage of real-time health monitoring, predictive analytics, robotic surgery, and AI medical imaging. - Provides insights into preventing drug counterfeiting, managing pharmaceutical cold chains, and optimizing supply chains. - Comprises a comparative analysis of global healthcare systems, telemedicine evolution, and future digital health trends.
Anindya Nag obtained an M.Sc. in Computer Science and Engineering from Khulna University in Khulna, Bangladesh, and a B.Tech. in Computer Science and Engineering from Adamas University in Kolkata, India. He is currently a lecturer in the Department of Computer Science and Engineering at the Northern University of Business and Technology in Khulna, Khulna 9100, Bangladesh. His research focuses on health informatics, medical Internet of Things, neuroscience, and machine learning. He serves as a reviewer for numerous prestigious journals and international conferences. He has authored and co-authored about 60 publications, including journal articles, conference papers, and book chapters, and has co-edited books. Md. Mehedi Hassan is currently a Ph.D. researcher in STEM (Computer and Information Science) at the University of South Australia, working on a fully funded research project. He started his Ph.D. in 2025, building on a strong academic background in computer science and engineering. He holds an M.Sc. in Computer Science and Engineering from Khulna University, Bangladesh, completed in 2024, and a B.Sc. in Computer Science and Engineering from North Western University, completed in 2022. His research spans computer science engineering and data science, with a strong focus on predictive analysis and expert system development. Md. Mehedi Hassan has authored 73 research papers and edited 5 books, actively contributing to the academic community. He serves as a peer reviewer for over 80 prestigious journals and collaborates extensively in interdisciplinary research. As a trainer for the VCourse platform, he has educated over 250 students over the past two years, sharing knowledge in emerging technologies and research methodologies. Beyond publications, he has actively engaged in intellectual property development, with several patents filed and three already granted in his name. His current research interests include computational neuroscience, machine learning for healthcare, and predictive modeling for biometrics. Dr. Riya Sil is an Associate Professor in Department of Computer Science & Engineering, Brainware University, Kolkata, India. Dr. Riya Sil holds a B.Tech & M.Tech degree in Computer Science & Engineering from Birla Institute of Technology and a PhD degree with a specialization in Legal Analytics. She has a total professional experience of about 9 years, including 7 years in academics and 2 years as Software Developer at Cognizant Technology Solutions (CTS). During her academic tenure, she has served as Asst. Professor in Computer Science & Engineering department in various institutions like Kristu Jayanti College - Autonomous, Techno India University, and Adamas University. Her research focuses on Machine Learning; Natural Language Processing (NLP); Deep Learning; Artificial Intelligence (AI) and Cloud Computing. She serves as a reviewer for various reputable journals and international conferences. She has about 40 publications to her credit which include peer-reviewed SCI and Scopus-indexed journals, conferences and book chapters. Dr. Asif Karim currently works at the Faculty of Science and Technology, Charles Darwin University. Asif does research in Machine Learning based Health Informatics and Blockchain Applications. He has considerable Industry Experience in the field of IT, primarily in Software Engineering. Complete Information about his Research Publications, Teaching and Grants are available at https://asifkarim.com/.
Preface. 1. Global Healthcare System and Industry Evaluation. 2. Development of Active Learning based Classification Modelfor Detection of Pneumonia using X-ray Image. 3. A Comprehensive Analysis of Artificial Intelligence Techniques for Automated Microaneurysm Detection. 4. Egret Swarm Optimization Algorithm-based Hybrid Deep Neural Network for Diagnosis of Skin Cancer. 5. MicrobiomeNet-X: An Ensemble Deep Learning Framework for Microbiome Therapies and Validation. 6. Applications and Challenges of Intelligent Decision Support Systems in Healthcare. 7. Artificial Intelligence Networking System for Smart Healthcare. 8. Quantum-resilient AI Networks with Heterogeneous Ensemble Deep Learning: A Unified Framework for Secure, Efficient and Explainable Health IoT Ecosystems. 9. Assessment of Real-time IoT-powered Wearables for Stress Level Detection and Therapy Support. 10. Big Data and IoT in Public Health Management. 11. Leveraging Big Data and IoT for Advanced Public Health Management. 12. A Comparative Study on Blockchain Architectures for Secure and Transparent Healthcare Systems. 13. Securing Healthcare Systems: A Deep Dive into NSL-KDD for Advanced Intrusion Detection. 14. Security and Privacy in Healthcare Systems. 15. Cyber-resilient Healthcare: Merging Usability, Efficiency, and Advanced Security Technologies. 16. Innovative Approaches to Healthcare Security: Balancing Technology, Privacy, and Ethical Oversight. 17. Green Healthcare and Sustainable Practices: A Path to a Resilient Future. Index. About the Editors.
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