Data Science for COVID-19 : Computational Perspectives /
Data Science for COVID-19 presents leading-edge research on data science techniques for the detection, mitigation, treatment and elimination of COVID-19. Sections provide an introduction to data science for COVID-19 research, considering past and future pandemics, as well as related Coronavirus vari...
| Main Authors: | , , , , |
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| Format: | software, multimedia |
| Language: | eng |
| Published: |
Amsterdam : Academic Press,
2021
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| Subjects: | |
| Online Access: | https://www.sciencedirect.com/science/book/9780128245361 |
| _version_ | 1796765060839768064 |
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| author | Kose, Utku, 1985-, editor 651210 Gupta, Deepak-, editor 636375 Albuquerque, Victor Hugo Costa de-, editor 651211 Khanna, Ashish-, editor 636376 ScienceDirect (Online service) 7722 |
| author_facet | Kose, Utku, 1985-, editor 651210 Gupta, Deepak-, editor 636375 Albuquerque, Victor Hugo Costa de-, editor 651211 Khanna, Ashish-, editor 636376 ScienceDirect (Online service) 7722 |
| author_sort | Kose, Utku, 1985-, editor 651210 |
| collection | OCEAN |
| description | Data Science for COVID-19 presents leading-edge research on data science techniques for the detection, mitigation, treatment and elimination of COVID-19. Sections provide an introduction to data science for COVID-19 research, considering past and future pandemics, as well as related Coronavirus variations. Other chapters cover a wide range of Data Science applications concerning COVID-19 research, including Image Analysis and Data Processing, Geoprocessing and tracking, Predictive Systems, Design Cognition, mobile technology, and telemedicine solutions. The book then covers Artificial Intelligence-based solutions, innovative treatment methods, and public safety. Finally, readers will learn about applications of Big Data and new data models for mitigation. |
| first_indexed | 2024-03-05T17:18:51Z |
| format | software, multimedia |
| id | KOHA-OAI-TEST:605988 |
| institution | Universiti Teknologi Malaysia - OCEAN |
| language | eng |
| last_indexed | 2024-03-05T17:18:51Z |
| publishDate | 2021 |
| publisher | Amsterdam : Academic Press, |
| record_format | dspace |
| spelling | KOHA-OAI-TEST:6059882023-10-10T07:30:42ZData Science for COVID-19 : Computational Perspectives / Kose, Utku, 1985-, editor 651210 Gupta, Deepak-, editor 636375 Albuquerque, Victor Hugo Costa de-, editor 651211 Khanna, Ashish-, editor 636376 ScienceDirect (Online service) 7722 software, multimedia Electronic books 631902 Amsterdam : Academic Press,©20212021engData Science for COVID-19 presents leading-edge research on data science techniques for the detection, mitigation, treatment and elimination of COVID-19. Sections provide an introduction to data science for COVID-19 research, considering past and future pandemics, as well as related Coronavirus variations. Other chapters cover a wide range of Data Science applications concerning COVID-19 research, including Image Analysis and Data Processing, Geoprocessing and tracking, Predictive Systems, Design Cognition, mobile technology, and telemedicine solutions. The book then covers Artificial Intelligence-based solutions, innovative treatment methods, and public safety. Finally, readers will learn about applications of Big Data and new data models for mitigation.Includes bibliographical references and index1. Predictive models to the COVID-19 -- 2. An artificial intelligence–based decision support and resource management system for COVID-19 pandemic -- 3. Normalizing images is good to improve computer-assisted COVID-19 diagnosis -- 4. Detection and screening of COVID-19 through chest computed tomography radiographs using deep neural networks. -- 5. Differential evolution to estimate the parameters of a SEIAR model with dynamic social distancing: the case of COVID-19 in Italy -- 6. Limitations and challenges on the diagnosis of COVID-19 using radiology images and deep learning -- 7. Deep convolutional neural network–based image classification for COVID-19 diagnosis -- 8. Statistical machine learning forecasting simulation for discipline prediction and cost estimation of COVID-19 pandemic -- 9. Application of machine learning for the diagnosis of COVID-19 -- 10. PwCOV in cluster-based web server: an assessment of service-oriented computing for COVID-19 disease processing system -- 11. COVID-19–affected medical image analysis using DenserNet -- 12. uTakeCare: unlock full decentralization of personal data for a respectful decontainment in the context of COVID-19: toward a digitally empowered anonymous citizenship- -- 13. COVID-19 detection from chest X-rays using transfer learning with deep convolutional neural networks -- 14. Lexicon-based sentiment analysis using Twitter data: a case of COVID-19 outbreak in India and abroad -- 15. Real-time social distance alerting and contact tracing using image processing -- 16. Machine-learning models for predicting survivability in COVID-19 patients -- 17. Robust and secured telehealth system for COVID-19 patients -- 18. A novel approach to predict COVID-19 using support vector machine -- 19. An ensemble predictive analytics of COVID-19 infodemic tweets using bag of words -- 20. Forecast and prediction of COVID-19 using machine learning -- 21 - Time series analysis of the COVID-19 pandemic in Australia using genetic programming -- 22. Image analysis and data processing for COVID-19 -- 23. A demystifying convolutional neural networks using Grad-CAM for prediction of coronavirus disease (COVID-19) on X-ray images -- 24. Transfer learning-based convolutional neural network for COVID-19 detection with X-ray images -- 25. Computational modeling of the pharmacological actions of some antiviral agents against SARS-CoV-2 -- 26 - Received signal strength indication—based COVID-19 mobile application to comply with social distancing using bluetooth signals from smartphones -- 27. COVID-19 pandemic in India: Forecasting using machine learning techniques -- 28. Mathematical recipe for curbing coronavirus (COVID-19) transmition dynamics -- 29. Sliding window time series forecasting with multilayer perceptron and multiregression of COVID-19 outbreak in Malaysia -- 30. A two-level deterministic reasoning pattern to curb the spread of COVID-19 in Africa -- 31. Data-driven approach to COVID-19 infection forecast for Nigeria using negative binomial regression model -- 32. A novel machine learning–based detection and diagnosis model for coronavirus disease (COVID-19) using discrete wavelet transform with rough neural network -- 33. Artificial intelligence–based solutions for early identification and classification of COVID-19 and acute respiratory distress syndrome -- 34. Internet of Medical Things (IoMT) with machine learning–based COVID-19 diagnosis model using chest X-ray images -- 35. The growth of COVID-19 in Spain. A view based on time-series forecasting methods -- 36. On privacy enhancement using u-indistinguishability to COVID-19 contact tracing approach in Korea -- 37. Scheduling shuttle ambulance vehicles for COVID-19 quarantine cases, a multi-objective multiple 0–1 knapsack model with a novel Discrete Binary Gaining-Sharing knowledge-based optimization algorithm.Data Science for COVID-19 presents leading-edge research on data science techniques for the detection, mitigation, treatment and elimination of COVID-19. Sections provide an introduction to data science for COVID-19 research, considering past and future pandemics, as well as related Coronavirus variations. Other chapters cover a wide range of Data Science applications concerning COVID-19 research, including Image Analysis and Data Processing, Geoprocessing and tracking, Predictive Systems, Design Cognition, mobile technology, and telemedicine solutions. The book then covers Artificial Intelligence-based solutions, innovative treatment methods, and public safety. Finally, readers will learn about applications of Big Data and new data models for mitigation.COVID-19 (Disease)Medical mappinghttps://www.sciencedirect.com/science/book/9780128245361URN:ISBN:9780128245361Remote access restricted to users with a valid UTM ID via VPN. |
| spellingShingle | COVID-19 (Disease) Medical mapping Kose, Utku, 1985-, editor 651210 Gupta, Deepak-, editor 636375 Albuquerque, Victor Hugo Costa de-, editor 651211 Khanna, Ashish-, editor 636376 ScienceDirect (Online service) 7722 Data Science for COVID-19 : Computational Perspectives / |
| title | Data Science for COVID-19 : Computational Perspectives / |
| title_full | Data Science for COVID-19 : Computational Perspectives / |
| title_fullStr | Data Science for COVID-19 : Computational Perspectives / |
| title_full_unstemmed | Data Science for COVID-19 : Computational Perspectives / |
| title_short | Data Science for COVID-19 : Computational Perspectives / |
| title_sort | data science for covid 19 computational perspectives |
| topic | COVID-19 (Disease) Medical mapping |
| url | https://www.sciencedirect.com/science/book/9780128245361 |
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