Description

Book Synopsis

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

Intelligent Computing Applications for COVID19

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    A Hardback by Tanzila Saba, Amjad Rehman Khan

    £135.00

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      Book details

      Publisher Taylor & Francis
      Published 8 September 2021
      ISBN-13 9780367692476
      978-0367692476
      ISBN-10 0367692473

      Description

      Book Synopsis

      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

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