The Prediction of Future Pandemics
Artificial Intelligence and Nanotechnology Approaches
- 1st Edition - June 1, 2025
- Editors: Ali Ahmadian, Ferial Ghaemi, Ashok Kumar Yadav, M.J. Ebadi, Soheil Salahshour
- Language: English
- Paperback ISBN:9 7 8 - 0 - 4 4 3 - 3 3 8 7 1 - 7
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 3 3 8 7 2 - 4
Prediction of the Future Pandemic: Artificial Intelligence and Nanotechnology Approaches provides a comprehensive account of the applications, challenges, and breakthroughs in usi… Read more
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Request a sales quote- Offers an in-depth examination of the integration of AI and nanotechnology in pandemic prediction
- Covers many nanotechnology applications in pandemic prediction, such as nanorobotics for targeted intervention, the role of nanomaterials in prevention strategies, viral detection/nanosensors in quarantine enforcement, and nanocomposite resilience (building pandemic-proof materials)
- Helps readers get to grips with the fast-evolving landscape of AI, nanotechnology, and global health
- Covers both the theory and real-world applications of AI and nanotechnology in predicting pandemics
- Discusses the fast-changing connection between AI, nanotechnology, and pandemic prediction
2. Interdisciplinary Perspectives on Future Pandemic Prediction
3. Role of Artificial Intelligence in Pandemic Prediction
4. Nanotechnology Applications in Pandemic Prediction
5. AI and Nanotechnology Integration and Future Pandemic Prediction
6. Comparative Analysis of AI and Nanotech Approaches for Pandemic Prediction
7. Quantum Leaps in Pandemic Prediction: AI Synergy
8. AI Healers: Redefining Pandemic Response
9. Role of Nanomaterials in Prevention Strategies
10. Viral Detection: Nanosensors in Quarantine Enforcement
11. Future Implications, Opportunities and Limitations in Pandemic Prediction
12. Pandemics of Tomorrow: How AI and Nanotech will Transform Global Health?
- No. of pages: 400
- Language: English
- Edition: 1
- Published: June 1, 2025
- Imprint: Elsevier
- Paperback ISBN: 9780443338717
- eBook ISBN: 9780443338724
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Ali Ahmadian
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Ferial Ghaemi
Dr. Ferial Ghaemi is a postdoctoral research fellow at RMIT University's Melbourne campus. As an experienced researcher and lecturer with a demonstrated history in higher education and industry, she is dedicated to advancing research in nanotechnology. She holds a Ph.D. in nanotechnology, with a specialized focus on the fabrication of nanomaterials and analytical chemistry.
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Ashok Kumar Yadav
Dr. Ashok Kumar Yadav holds a B.Tech. from AKTU Lucknow and an M.Tech. and Ph.D. from JNU New Delhi, India. With over eight years of combined teaching and research experience, he is currently an Assistant Professor in the Department of Information Technology at Rajkiya Engineering College, Azamgarh, India. Before this, he served as an Assistant Professor (On ad-hoc) at the University of Delhi. Dr. Yadav's research expertise spans across multi-attribute decision-making (MADM), blockchain technology, machine learning, and mobility management in mobile communication. His significant contributions include publications in renowned journals such as Elsevier, Springer, World Scientific, and Taylor & Francis, as well as presentations at prominent international conferences. Among his notable works, Dr. Yadav is the author of "Blockchain Technology and Its Applications" and co-author of "Mastering Disruptive Technologies: Applications of Cloud Computing, IoT, Blockchain, Artificial Intelligence & Machine Learning Techniques." Additionally, he has edited two books for IGI Global. Dr. Yadav's academic achievements include six SCI-indexed publications, two Scopus-indexed papers, and six patents. He is actively involved in academia as a reviewer for international journals and a contributor to program committees at various conferences. His excellence has been recognized with the Best Paper Award at the IEEE World Conference on Applied Intelligence and Computing in 2022, and at the International Conference on Artificial Intelligence and Smart Communication (AISC) in 2023.
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M.J. Ebadi
Dr M. J. Ebadi obtained a Ph.D. degree in applied mathematics in 2018. Dr Ebadi’s research interests span a wide range of topics, including artificial intelligence, neural networks, deep learning, numerical optimization, optimal control, numerical analysis, fractional calculus, and fuzzy mathematics.
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