Computational Modeling and Data Analysis in COVID-19 Research Computational Modeling and Data Analysis in COVID-19 Research
Emerging Trends in Biomedical Technologies and Health informatics

Computational Modeling and Data Analysis in COVID-19 Research

    • $99.99
    • $99.99

Publisher Description

This book covers recent research on the COVID-19 pandemic. It includes the analysis, implementation, usage, and proposed ideas and models with architecture to handle the COVID-19 outbreak. Using advanced technologies such as artificial intelligence (AI) and machine learning (ML), techniques for data analysis, this book will be helpful to mitigate exposure and ensure public health. We know prevention is better than cure, so by using several ML techniques, researchers can try to predict the disease in its early stage and develop more effective medications and treatments. Computational technologies in areas like AI, ML, Internet of Things (IoT), and drone technologies underlie a range of applications that can be developed and utilized for this purpose. Because in most cases there is no one solution to stop the spreading of pandemic diseases, and the integration of several tools and tactics are needed. Many successful applications of AI, ML, IoT, and drone technologies already exist, including systems that analyze past data to predict and conclude some useful information for controlling the spread of COVID-19 infections using minimum resources. The AI and ML approach can be helpful to design different models to give a predictive solution for mitigating infection and preventing larger outbreaks. This book:
Examines the use of artificial intelligence (AI), machine learning (ML), Internet of Things (IoT), and drone technologies as a helpful predictive solution for controlling infection of COVID-19 Covers recent research related to the COVID-19 pandemic and includes the analysis, implementation, usage, and proposed ideas and models with architecture to handle a pandemic outbreak Examines the performance, implementation, architecture, and techniques of different analytical and statistical models related to COVID-19 Includes different case studies on COVID-19
Dr. Chhabi Rani Panigrahi is Assistant Professor in the Department of Computer Science at Rama Devi Women’s University, Bhubaneswar, India.

Dr. Bibudhendu Pati is Associate Professor and Head of the Department of Computer Science at Rama Devi Women’s University, Bhubaneswar, India.

Dr. Mamata Rath is Assistant Professor in the School of Management (Information Technology) at Birla Global University, Bhubaneswar, India.

Prof. Rajkumar Buyya is a Redmond Barry Distinguished Professor and Director of the Cloud Computing and Distributed Systems (CLOUDS) Laboratory at the University of Melbourne, Australia.

GENRE
Professional & Technical
RELEASED
2021
9 May
LANGUAGE
EN
English
LENGTH
270
Pages
PUBLISHER
CRC Press
SELLER
Taylor & Francis Group
SIZE
13.1
MB
Evolution of Machine Learning and Internet of Things Applications in Biomedical Engineering Evolution of Machine Learning and Internet of Things Applications in Biomedical Engineering
2024
Computational Approaches in Biotechnology and Bioinformatics Computational Approaches in Biotechnology and Bioinformatics
2024
Computational Approaches in Biomaterials and Biomedical Engineering Applications Computational Approaches in Biomaterials and Biomedical Engineering Applications
2024
Healthcare Services in the Metaverse Healthcare Services in the Metaverse
2024
Deep Learning in Biomedical and Health Informatics Deep Learning in Biomedical and Health Informatics
2021
Machine Learning and Deep Learning in Efficacy Improvement of Healthcare Systems Machine Learning and Deep Learning in Efficacy Improvement of Healthcare Systems
2022