Assessing COVID-19 and Other Pandemics and Epidemics using Computational Modelling and Data Analysis

Assessing COVID-19 and Other Pandemics and Epidemics using Computational Modelling and Data Analysis

This book comprehensively covers the topic of COVID-19 and other pandemics and epidemics data analytics using computational modelling. Biomedical and Health Informatics is an emerging field of research at the intersection of information science, computer science, and health care. The new era of pand...

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Bibliographic Details
Other Authors / Creators:Pani, Subhendu Kumar. editor.
Dash, Sujata. editor.
dos Santos, Wellington P. editor.
Chan Bukhari, Syed Ahmad. editor.
Flammini, Francesco. editor.
Other Corporate Authors / Creators:SpringerLink (Online service)
Format: Electronic eBook
Language:English
Edition:1st ed. 2022.
Imprint: Cham : Springer International Publishing : Imprint: Springer, 2022.
Subjects:
Artificial intelligence.
Quantitative research.
Cooperating objects (Computer systems).
Internet of things.
Public health.
Diseases—Animal models.
Artificial Intelligence.
Data Analysis and Big Data.
Cyber-Physical Systems.
Internet of Things.
Public Health.
Disease Models.
Online Access:Available in Springer Computer Science eBooks 2022 English/International.
Table of Contents:
  • Chapter 1 Artificial Intelligence (AI) and Big Data Analytics for COVID-19 Pandemic
  • Chapter 2 COVID-19 TravelCover Post-lockdown Smart Transportation Management System for COVID-19
  • Chapter 3 Diverse techniques applied for effective diagnosis of COVID 19
  • Chapter 4 A Review on Detection of Covid-19 Patients using Deep Learning Techniques.-Chapter 5 Internet of Health Things (IoHT) for COVID 19
  • Chapter 6 Diagnosis for COVID-19
  • Chapter 7 IoT in Combating Covid 19 Pandemics Lessons for Developing Countries
  • Chapter 8 Machine learning approaches for COVID 19 pandemic
  • Chapter 9 Smart sensing for COVID 19 Pandemic
  • Chapter 10 eHealth, mHealth and Telemedicine for COVID-19 pandemic
  • Chapter 11 Prediction of care for patients in a Covid-19 pandemic situation based on haematological parameters
  • Chapter 12 Bioinformatics in Diagnosis of Covid-19
  • Chapter 13 Predicting the Covid-19 Morbidity Outspread and Mortality Using Deep Learning Techniques
  • Chapter 14 LSTM -CNN Deep learning Based Hybrid system for real time COVID-19 data analysis and prediction using Twitter data
  • Chapter 15 An intelligent tool to support diagnosis of Covid-19 by texture analysis of computerized tomography x-ray images and machine learning
  • Chapter 16 Analysis of Blockchain Backed Covid19 Data
  • Chapter 17 Intelligent systems for dengue, chikungunya and zika temporal and spatio-temporal forecasting a contribution and a brief review
  • Chapter 18 Machine learning approaches for temporal and spatio-temporal Covid-19 forecasting a brief review and a contribution
  • Chapter 19 Image Reconstruction for COVID-19 using Multi-frequency Electrical Impedance Tomography.

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