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              <text>Cyber-Physical Systems: AI and COVID-19</text>
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              <text>Cyber-Physical Systems: AI and COVID-19 highlights original research which addresses current data challenges in terms of the development of mathematical models, cyber-physical systems-based tools and techniques, and the design and development of algorithmic solutions, etc. It reviews the technical concepts of gathering, processing and analyzing data from cyber-physical systems (CPS) and reviews tools and techniques that can be used. This book will act as a resource to guide COVID researchers as they move forward with clinical and epidemiological studies on this outbreak, including the technical concepts of gathering, processing and analyzing data from cyber-physical systems (CPS). The major problem in the identification of COVID-19 is detection and diagnosis due to non-availability of medicine. In this situation, only one method, Reverse Transcription Polymerase Chain Reaction (RT-PCR) has been widely adopted and used for diagnosis. With the evolution of COVID-19, the global research community has implemented many machine learning and deep learning-based approaches with incremental datasets. However, finding more accurate identification and prediction methods are crucial at this juncture.  2022 Elsevier Inc. All rights reserved.</text>
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              <text>Poonia R.C.; Agarwal B.; Kumar S.; Khan M.S.; Marques G.; Nayak J.</text>
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              <text>Cyber-Physical Systems: AI and COVID-19, pp. 1-260.</text>
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              <text>&lt;a href="https://doi.org/10.1016/C2020-0-02352-2" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1016/C2020-0-02352-2&lt;/a&gt;
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              <text>ISBN: 978-012824557-6; 978-032385357-6</text>
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              <text>Poonia R.C., Department of Computer Science, CHRIST (Deemed to be University), Bangalore, India; Agarwal B., Department of Computer Science and Engineering, Indian Institute of Information Technology (IIIT Kota), Kota, India; Kumar S., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Bengaluru, India; Khan M.S., Network Science and Analysis Lab (NSAL), Department of Computing, East Tennessee State University, Johnson City, TN, United States; Marques G., Polytechnic of Coimbra, ESTGOH, Rua General Santos Costa, Oliveira do Hospital, Portugal; Nayak J., Aditya Institute of Technology and Management, Autonomous Institution), K Kotturu, Tekkali, India</text>
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