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.
General
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