Intelligent Modeling, Prediction, and Diagnosis from Epidemiological Data Intelligent Modeling, Prediction, and Diagnosis from Epidemiological Data
Chapman & Hall/CRC Computational Intelligence and Its Applications

Intelligent Modeling, Prediction, and Diagnosis from Epidemiological Data

COVID-19 and Beyond

    • $109.99
    • $109.99

Publisher Description

Intelligent Modeling, Prediction, and Diagnosis from Epidemiological Data: COVID-19 and Beyond is a handy treatise to elicit and elaborate possible intelligent mechanisms for modeling, prediction, diagnosis, and early detection of diseases arising from outbreaks of different epidemics with special reference to COVID-19. Starting with a formal introduction of the human immune systems, this book focuses on the epidemiological aspects with due cognizance to modeling, prevention, and diagnosis of epidemics. In addition, it also deals with evolving decisions on post-pandemic socio-economic structure.

The book offers a comprehensive coverage of the most essential topics, including:
A general overview of pandemics and their outbreak behavior A detailed overview of CI techniques Intelligent modeling, prediction, and diagnostic measures for pandemics Prognostic models Post-pandemic socio-economic structure
The accompanying case studies are based on available real-world data sets.

While other books may deal with this COVID-19 pandemic, none features topics covering the human immune system as well as influences on the environmental disorder due to the ongoing pandemic.

The book is primarily intended to benefit medical professionals and healthcare workers as well as the virologists who are essentially the frontline fighters of this pandemic. In addition, it also serves as a vital resource for relevant researchers in this interdisciplinary field as well as for tutors and postgraduate and undergraduate students of information sciences.

GENRE
Professional & Technical
RELEASED
2021
22 November
LANGUAGE
EN
English
LENGTH
232
Pages
PUBLISHER
CRC Press
SELLER
Taylor & Francis Group
SIZE
18.7
MB
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