Intelligent Computing Applications for COVID-19 - Saba, Tanzila; Khan, Amjad Rehman; (ed.) - Prospero Internet Bookshop

Intelligent Computing Applications for COVID-19: Predictions, Diagnosis, and Prevention
 
Product details:

ISBN13:9780367692483
ISBN10:0367692481
Binding:Paperback
No. of pages:344 pages
Size:234x156 mm
Weight:480 g
Language:English
Illustrations: 128 Illustrations, black & white; 13 Halftones, black & white; 115 Line drawings, black & white; 56 Tables, black & white
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Category:

Intelligent Computing Applications for COVID-19

Predictions, Diagnosis, and Prevention
 
Edition number: 1
Publisher: CRC Press
Date of Publication:
 
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Short description:

This book provides insight into the recent advances of applications, statistical methods, and mathematical modeling for the healthcare industry.

Long description:

Accurate estimation, diagnosis, and prevention of COVID-19 is a global challenge for healthcare organizations. Innovative measures can introduce and implement AI, and Mathematical Modeling applications. This book provides insight into the recent advances of applications, statistical methods, and mathematical modeling for the healthcare industry.


This book covers the state-of-the-art applications of AI and Machine Learning in past epidemics, pandemics, and COVID-19. It offers recent global case studies, and discusses how AI and statistical methods, initiatives, and applications such as Machine Learning, Deep Learning, Correlation and Regression Analysis play a major role in the prediction, diagnosis, and prevention of a pandemic. It will also focus on how AI and statistical applications can facilitate and restructure the healthcare system.


This book is written for Researchers, Students, Professionals, Executives, and the general public.

Table of Contents:

Chapter 1


Deep Learning for COVID-19 Infection?s Diagnosis,  Prevention, and Treatment


Chapter 2


Artificial Intelligence in Coronavirus Detection?Recent Findings and Future Perspectives


Chapter 3


Solutions of Differential Equations for Prediction of COVID-19 Cases by Homotopy Perturbation Method


Chapter 4


Predictive Models of Hospital Readmission Rate Using the Improved AdaBoost in COVID-19


Chapter 5


Nigerian Medical Laboratory Diagnosis of COVID-19; from Grass to Grace


Chapter 6


COVID-19 CT Image Segmentation and Detection: Review


Chapter 7


Interactive Medical Chatbot for Assisting with COVID-related Queries


Chapter 8


COVID-19 Outbreak Prediction After Lockdown, Based on Current Data Analytics


Chapter 9


A Deep Learning CNN Model for Genome Sequence Classification


Chapter 10


The Impact of Lockdown Strategies on COVID-19 Cases with a Confined Sentiment Analysis of COVID-19 Tweets


Chapter 11


A Mathematical Model and Forecasting of COVID-19 Outbreak in India


Chapter 12


Automatic Lung Infection Segmentation of COVID-19 in CT Scan Images


Chapter 13


A Review of Feature Selection Algorithms in Determining the Factors Affecting COVID-19


Chapter 14


 Industry 4.0 Technology-based Diagnosis for COVID-19


Index