Cover for Data Science for COVID-19

Data Science for COVID-19

Computational Perspectives

Book2021

Edited by:

Utku Kose, Deepak Gupta, ... Ashish Khanna

Data Science for COVID-19

Computational Perspectives

Book2021

 

Cover for Data Science for COVID-19

Edited by:

Utku Kose, Deepak Gupta, ... Ashish Khanna

About the book

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Book 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 introd ... read full description

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  2. Book chapterAbstract only

    1 - Predictive models to the COVID-19

    Francisco Nauber Bernardo Gois, Alex Lima, ... João Alexandre Lôbo Marques

    Pages 1-24

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    2 - An artificial intelligence–based decision support and resource management system for COVID-19 pandemic

    Enis Karaarslan and Doğan Aydın

    Pages 25-49

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    3 - Normalizing images is good to improve computer-assisted COVID-19 diagnosis

    Claudio Filipi Gonçalves dos Santos, Leandro Aparecido Passos, ... João Paulo Papa

    Pages 51-62

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    4 - Detection and screening of COVID-19 through chest computed tomography radiographs using deep neural networks.

    Khushboo Munir, Hassan Elahi, ... Antonello Rizzi

    Pages 63-73

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    5 - Differential evolution to estimate the parameters of a SEIAR model with dynamic social distancing: the case of COVID-19 in Italy

    I. De Falco, A. Della Cioppa, ... E. Tarantino

    Pages 75-90

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    6 - Limitations and challenges on the diagnosis of COVID-19 using radiology images and deep learning

    Merve Ayyuce Kızrak, Zümrüt Müftüoğlu and Tülay Yıldırım

    Pages 91-115

  8. Book chapterAbstract only

    7 - Deep convolutional neural network–based image classification for COVID-19 diagnosis

    R.M. Tharsanee, R.S. Soundariya, ... S. Sountharrajan

    Pages 117-145

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    8 - Statistical machine learning forecasting simulation for discipline prediction and cost estimation of COVID-19 pandemic

    Papri Ghosh and Ritam Dutta

    Pages 147-173

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    9 - Application of machine learning for the diagnosis of COVID-19

    Prajoy Podder, Subrato Bharati, ... Utku Kose

    Pages 175-194

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    10 - PwCOV in cluster-based web server: an assessment of service-oriented computing for COVID-19 disease processing system

    Abhijit Bora and Tulshi Bezboruah

    Pages 195-212

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    11 - COVID-19–affected medical image analysis using DenserNet

    Chandranath Adak, Debmitra Ghosh, ... Soumi Chattopadhyay

    Pages 213-230

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    12 - uTakeCare: unlock full decentralization of personal data for a respectful decontainment in the context of COVID-19: toward a digitally empowered anonymous citizenship

    Lamine Amour, Matthieu Quiniou, ... Sami Souihi

    Pages 231-253

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    13 - COVID-19 detection from chest X-rays using transfer learning with deep convolutional neural networks

    Prasitthichai Naronglerdrit, Iosif Mporas and Akbar Sheikh-Akbari

    Pages 255-273

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    14 - Lexicon-based sentiment analysis using Twitter data: a case of COVID-19 outbreak in India and abroad

    H.S. Hota, Dinesh K. Sharma and Nilesh Verma

    Pages 275-295

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    15 - Real-time social distance alerting and contact tracing using image processing

    Balaji Muthazhagan, Aparnasri Panchapakesan and Suriya Sundaramoorthy

    Pages 297-315

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    16 - Machine-learning models for predicting survivability in COVID-19 patients

    Ijegwa David Acheme and Olufunke Rebecca Vincent

    Pages 317-336

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    17 - Robust and secured telehealth system for COVID-19 patients

    Waheed Ullah, Abid Yahya, ... Taolo Tlale

    Pages 337-349

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    18 - A novel approach to predict COVID-19 using support vector machine

    Soham Guhathakurata, Souvik Kundu, ... Jyoti Sekhar Banerjee

    Pages 351-364

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    19 - An ensemble predictive analytics of COVID-19 infodemic tweets using bag of words

    T.O. Olaleye, O.T. Arogundade, ... A.K. Adesemowo

    Pages 365-380

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    20 - Forecast and prediction of COVID-19 using machine learning

    Deepak Painuli, Divya Mishra, ... Mayank Aggarwal

    Pages 381-397

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    21 - Time series analysis of the COVID-19 pandemic in Australia using genetic programming

    Rohit Salgotra and Amir H. Gandomi

    Pages 399-411

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    22 - Image analysis and data processing for COVID-19

    Ambeshwar Kumar, R. Manikandan, ... Deepak Gupta

    Pages 413-427

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    23 - A demystifying convolutional neural networks using Grad-CAM for prediction of coronavirus disease (COVID-19) on X-ray images

    C.V. Aravinda, Meng Lin, ... G. Amar Prabhu

    Pages 429-450

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    24 - Transfer learning-based convolutional neural network for COVID-19 detection with X-ray images

    Kevser Sahinbas and Ferhat Ozgur Catak

    Pages 451-466

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    25 - Computational modeling of the pharmacological actions of some antiviral agents against SARS-CoV-2

    Abayomi Emmanuel Adegboyega, Titilayo Omolara Johnson and Simeon Omale

    Pages 467-482

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    26 - Received signal strength indication—based COVID-19 mobile application to comply with social distancing using bluetooth signals from smartphones

    Alvaro Aspilcueta Narvaez and Jorge Guerra Guerra

    Pages 483-501

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    27 - COVID-19 pandemic in India: Forecasting using machine learning techniques

    H.S. Hota, Richa Handa and A.K. Shrivas

    Pages 503-525

  29. Book chapterAbstract only

    28 - Mathematical recipe for curbing coronavirus (COVID-19) transmition dynamics

    Emmanuel Bala Gudu, Daniel Dauda Wisdom, ... Ebenezer Ajayi Akinyemi

    Pages 527-545

  30. Book chapterAbstract only

    29 - Sliding window time series forecasting with multilayer perceptron and multiregression of COVID-19 outbreak in Malaysia

    Norita Md Norwawi

    Pages 547-564

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    30 - A two-level deterministic reasoning pattern to curb the spread of COVID-19 in Africa

    Olumide Mohammed Lawal and Olufunke Rebecca Vincent

    Pages 565-581

  32. Book chapterAbstract only

    31 - Data-driven approach to COVID-19 infection forecast for Nigeria using negative binomial regression model

    Chollette C. Olisah, Olusoji O. Ilori, ... Victor T. Odumuyiwa

    Pages 583-596

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    32 - A novel machine learning–based detection and diagnosis model for coronavirus disease (COVID-19) using discrete wavelet transform with rough neural network

    Irina Valeryevna Pustokhina, Denis Alexandrovich Pustokhin and K. Shankar

    Pages 597-612

  34. Book chapterAbstract only

    33 - Artificial intelligence–based solutions for early identification and classification of COVID-19 and acute respiratory distress syndrome

    Sujathakrishamoorthy, Surapaneni Krishna Mohan, ... M. Lorate Shiny

    Pages 613-626

  35. Book chapterAbstract only

    34 - Internet of Medical Things (IoMT) with machine learning–based COVID-19 diagnosis model using chest X-ray images

    S. Sheeba Rani, S. Selvakumar, ... E. Dhiravida Chelvi

    Pages 627-641

  36. Book chapterAbstract only

    35 - The growth of COVID-19 in Spain. A view based on time-series forecasting methods

    Andrés Carrión-García, José Jabaloyes and Angela Grisales

    Pages 643-660

  37. Book chapterAbstract only

    36 - On privacy enhancement using u-indistinguishability to COVID-19 contact tracing approach in Korea

    Hyoung Joong Kim, Suah Kim and Sungho Lee

    Pages 661-673

  38. Book chapterAbstract only

    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

    Said Ali Hassan, Prachi Agrawal, ... Ali Wagdy Mohamed

    Pages 675-698

  39. Book chapterNo access

    Index

    Pages 699-717

About the book

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.

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

  • 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
  • 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

Details

ISBN

978-0-12-824536-1

Language

English

Published

2021

Copyright

Copyright © 2021 Elsevier Inc. All rights reserved.

Imprint

Academic Press

Editors

Utku Kose

Deepak Gupta

Victor Hugo C. de Albuquerque

Ashish Khanna