Data Science for COVID-19 Volume 1
Computational Perspectives
- 1st Edition - May 20, 2021
- Latest edition
- Editors: Utku Kose, Deepak Gupta, Victor Hugo Costa de Albuquerque, Ashish Khanna
- Language: English
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 introd… Read more
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Description
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.
Key features
Key features
- Provides a leading-edge survey of Data Science techniques and methods for research, mitigation and treatment of the COVID-19 virus
- Integrates various Data Science techniques to provide a resource for COVID-19 researchers and clinicians around the world, including both positive and negative research findings
- Provides insights into innovative data-oriented modeling and predictive techniques from COVID-19 researchers
- Includes real-world feedback and user experiences from physicians and medical staff from around the world on the effectiveness of applied Data Science solutions
Readership
Readership
Table of contents
Table of contents
2. An AI 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 CT Radiographs Using Deep Neural Networks
5. Differential Evolution to improve the effectiveness of the epidemiological SEIR model enhanced with dynamic social distancing: the case of COVID-19 and 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 Denser Net
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 CNN
14. Lexicon Based Sentiment Analysis Using Twitter Data: A Case of COVID-19 Outbreak in India and Abroad
15. Real time social distancing 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 & 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 Gradcam 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 Modelling of the Pharmacological actions of some anti-viral agents against SARS-CoV-2
26. Mobile Technology Solutions for COVID-19: RSSI-based COVID-19 mobile app 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 Corona Virus (Covid-19) Transmition Dynamics
29. Sliding Window Time Series Forecasting with Multi-Layer Perceptron and Multi Regression 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 in Nigeria using negative binomial regression model
32. A Novel Machine Learning Based Detection and Diagnosis Model for Corona Virus Disease (Covid-19) using Discrete Wavelet Transform (DWT) with Rough Neural Network (RNN)
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 COVID19 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
Product details
Product details
- Edition: 1
- Latest edition
- Published: May 20, 2021
- Language: English
About the editors
About the editors
UK
Utku Kose
DG
Deepak Gupta
Dr. Aditya Khamparia has expertise in teaching, entrepreneurship, and research and development of 11 years. He is presently working as Assistant Professor in Babasaheb Bhimrao Ambedkar University, Satellite Centre, Amethi, India. He received his Ph.D. degree from Lovely Professional University, Punjab, India in May 2018. He has completed his M. Tech. from VIT University, Vellore, Tamil Nadu, India and B. Tech. from RGPV, Bhopal, Madhya Pradesh, India. He has completed his PDF from UNIFOR, Brazil. He has published around 105 research papers along with book chapters including more than 25 papers in SCI indexed Journals with cumulative impact factor of above 100 to his credit. Additionally, he has authored and edited eleven books. Furthermore, he has served the research field as a Keynote Speaker/Session Chair/Reviewer/TPC member/Guest Editor and many more positions in various conferences and journals. His research interest include machine learning, deep learning for biomedical health informatics, educational technologies, and computer vision.
Vd
Victor Hugo Costa de Albuquerque
AK
Ashish Khanna
Ashish Khanna is Professor in Department of Computer Science and Engineering, Maharaja Agrasen Institute of Technology, New Delhi, India, and is also a Visiting Professor at the University of Valladolid, Spain. His research interests include distributed systems, MANET, FANET, VANET, Internet of Things, and machine learning.