Dublin Core
Title
Computational Modelling and Imaging for SARS-CoV-2 and COVID-19
Subject
Computer Science, Engineering & Technology, Medicine, Dentistry, Nursing & Allied Health
Description
The aim of this book is to present new computational techniques and methodologies for the analysis of the clinical, epidemiological and public health aspects of SARS-CoV-2 and COVID-19 pandemic. The book presents the use of soft computing techniques such as machine learning algorithms for analysis of the epidemiological aspects of the SARS-CoV-2. This book clearly explains novel computational image processing algorithms for the detection of COVID-19 lesions in lung CT and X-ray images. It explores various computational methods for computerized analysis of the SARS-CoV-2 infection including severity assessment. The book provides a detailed description of the algorithms which can potentially aid in mass screening of SARS-CoV-2 infected cases. Finally the book also explains the conventional epidemiological models and machine learning techniques for the prediction of the course of the COVID-19 epidemic. It also provides real life examples through case studies. The book is intended for biomedical engineers, mathematicians, postgraduate students; researchers; medical scientists working on identifying and tracking infectious diseases.
Creator
S. Prabha, P. Karthikeyan, K. Kamalanand, N. Selvaganesan
Source
https://www.taylorfrancis.com/books/edit/10.1201/9781003142584/computational-modelling-imaging-sars-cov-2-covid-19-prabha-karthikeyan-kamalanand-selvaganesan?_gl=1*1tm19az*_ga*NjI1MDYwOTAzLjE3MDY1NzQzNDg.*_ga_0HYE8YG0M6*MTcwNzI2OTE2OS4zLjEuMTcwNzI2OTE4MC4wLjAuMA..&_ga=2.106153028.656743298.1707205995-625060903.1706574348
Publisher
Taylor & Francis
Date
2021
Contributor
Amalia TR
Format
PDF
Language
English
Type
Book
Identifier
https://doi.org/10.1201/9781003142584