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Intelligent data analysis for COVID-...
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Niranjanamurthy, M.
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Intelligent data analysis for COVID-19 pandemic
Record Type:
Electronic resources : Monograph/item
Title/Author:
Intelligent data analysis for COVID-19 pandemic/ edited by M. Niranjanamurthy, Siddhartha Bhattacharyya, Neeraj Kumar.
other author:
Niranjanamurthy, M.
Published:
Singapore :Springer Singapore : : 2021.,
Description:
xix, 370 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:
Chapter 1. Machine Learning Based Ensemble Approach for Predicting the Mortality Risk of Covid-19 Patients: A Case Study -- Chapter 2. The Role of Internet of Health Things (IoHTs) & Innovative Internet of 5G Medical Robotic Things (IIo-5GMRTs) in COVID-19 Global Health Risk Management and Logistics Planning -- Chapter 3. Battling COVID-19 with Process Model of Integrated Digital Technology: An Analysis of Qualitative Data -- Chapter 4. High-fidelity intelligence ventilator to help infect with Covid-19 based on artificial intelligence -- Chapter 5. Boon of Artificial Intelligence in Diagnosis of Covid-19 -- Chapter 6. Artificial Intelligence and Big Data Solutions for COVID-19 -- Chapter 7. Modeling the Transmition Dynamics of COVID-19 Virus Disease in Nigeria -- Chapter 8. Emerging Trends in Higher Education during Pandemic Covid-19: An impact study From West Bengal -- Chapter 9. COVID-19: Virology, Epidemiology, Diagnostics and Predictive modelling -- Chapter 10. Improved Estimation in Logistic Regression through Quadratic Bootstrap Approach: An Application in Indian Agricultural e-learning System during COVID-19 Pandemic -- Chapter 11. COVID-19 and Stock Markets: Deaths and Strict Policies -- Chapter 12. Artificial Intelligence Techniques in Medical Imaging for Detection of Corona Virus (COVID-19 / SARS-COV-2): A Brief Survey -- Chapter 13. A Travelling Disinfection-man Problem (TDP) for COVID-19: A Nonlinear Binary Constrained Gaining-Sharing knowledge-based Optimization Algorithm -- Chapter 14. COVID-19 Lock down Impact on Mental Health: A Cross-sectional Online Survey from Kerala, India -- Chapter 15. Analysis, Modelling and Prediction of COVID-19 Outbreaks using Machine Learning Algorithms.
Contained By:
Springer Nature eBook
Subject:
COVID-19 Pandemic, 2020- - Data processing. -
Online resource:
https://doi.org/10.1007/978-981-16-1574-0
ISBN:
9789811615740
Intelligent data analysis for COVID-19 pandemic
Intelligent data analysis for COVID-19 pandemic
[electronic resource] /edited by M. Niranjanamurthy, Siddhartha Bhattacharyya, Neeraj Kumar. - Singapore :Springer Singapore :2021. - xix, 370 p. :ill. (some col.), digital ;24 cm. - Algorithms for intelligent systems,2524-7565. - Algorithms for intelligent systems..
Chapter 1. Machine Learning Based Ensemble Approach for Predicting the Mortality Risk of Covid-19 Patients: A Case Study -- Chapter 2. The Role of Internet of Health Things (IoHTs) & Innovative Internet of 5G Medical Robotic Things (IIo-5GMRTs) in COVID-19 Global Health Risk Management and Logistics Planning -- Chapter 3. Battling COVID-19 with Process Model of Integrated Digital Technology: An Analysis of Qualitative Data -- Chapter 4. High-fidelity intelligence ventilator to help infect with Covid-19 based on artificial intelligence -- Chapter 5. Boon of Artificial Intelligence in Diagnosis of Covid-19 -- Chapter 6. Artificial Intelligence and Big Data Solutions for COVID-19 -- Chapter 7. Modeling the Transmition Dynamics of COVID-19 Virus Disease in Nigeria -- Chapter 8. Emerging Trends in Higher Education during Pandemic Covid-19: An impact study From West Bengal -- Chapter 9. COVID-19: Virology, Epidemiology, Diagnostics and Predictive modelling -- Chapter 10. Improved Estimation in Logistic Regression through Quadratic Bootstrap Approach: An Application in Indian Agricultural e-learning System during COVID-19 Pandemic -- Chapter 11. COVID-19 and Stock Markets: Deaths and Strict Policies -- Chapter 12. Artificial Intelligence Techniques in Medical Imaging for Detection of Corona Virus (COVID-19 / SARS-COV-2): A Brief Survey -- Chapter 13. A Travelling Disinfection-man Problem (TDP) for COVID-19: A Nonlinear Binary Constrained Gaining-Sharing knowledge-based Optimization Algorithm -- Chapter 14. COVID-19 Lock down Impact on Mental Health: A Cross-sectional Online Survey from Kerala, India -- Chapter 15. Analysis, Modelling and Prediction of COVID-19 Outbreaks using Machine Learning Algorithms.
This book presents intelligent data analysis as a tool to fight against COVID-19 pandemic. The intelligent data analysis includes machine learning, natural language processing, and computer vision applications to teach computers to use big data-based models for pattern recognition, explanation, and prediction. These functions are discussed in detail in the book to recognize (diagnose), predict, and explain (treat) COVID-19 infections, and help manage socio-economic impacts. It also discusses primary warnings and alerts; tracking and prediction; data dashboards; diagnosis and prognosis; treatments and cures; and social control by the use of intelligent data analysis. It provides analysis reports, solutions using real-time data, and solution through web applications details.
ISBN: 9789811615740
Standard No.: 10.1007/978-981-16-1574-0doiSubjects--Topical Terms:
3490700
COVID-19 Pandemic, 2020-
--Data processing.
LC Class. No.: RA644.C67 / I48 2021
Dewey Class. No.: 362.1962414
Intelligent data analysis for COVID-19 pandemic
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Chapter 1. Machine Learning Based Ensemble Approach for Predicting the Mortality Risk of Covid-19 Patients: A Case Study -- Chapter 2. The Role of Internet of Health Things (IoHTs) & Innovative Internet of 5G Medical Robotic Things (IIo-5GMRTs) in COVID-19 Global Health Risk Management and Logistics Planning -- Chapter 3. Battling COVID-19 with Process Model of Integrated Digital Technology: An Analysis of Qualitative Data -- Chapter 4. High-fidelity intelligence ventilator to help infect with Covid-19 based on artificial intelligence -- Chapter 5. Boon of Artificial Intelligence in Diagnosis of Covid-19 -- Chapter 6. Artificial Intelligence and Big Data Solutions for COVID-19 -- Chapter 7. Modeling the Transmition Dynamics of COVID-19 Virus Disease in Nigeria -- Chapter 8. Emerging Trends in Higher Education during Pandemic Covid-19: An impact study From West Bengal -- Chapter 9. COVID-19: Virology, Epidemiology, Diagnostics and Predictive modelling -- Chapter 10. Improved Estimation in Logistic Regression through Quadratic Bootstrap Approach: An Application in Indian Agricultural e-learning System during COVID-19 Pandemic -- Chapter 11. COVID-19 and Stock Markets: Deaths and Strict Policies -- Chapter 12. Artificial Intelligence Techniques in Medical Imaging for Detection of Corona Virus (COVID-19 / SARS-COV-2): A Brief Survey -- Chapter 13. A Travelling Disinfection-man Problem (TDP) for COVID-19: A Nonlinear Binary Constrained Gaining-Sharing knowledge-based Optimization Algorithm -- Chapter 14. COVID-19 Lock down Impact on Mental Health: A Cross-sectional Online Survey from Kerala, India -- Chapter 15. Analysis, Modelling and Prediction of COVID-19 Outbreaks using Machine Learning Algorithms.
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This book presents intelligent data analysis as a tool to fight against COVID-19 pandemic. The intelligent data analysis includes machine learning, natural language processing, and computer vision applications to teach computers to use big data-based models for pattern recognition, explanation, and prediction. These functions are discussed in detail in the book to recognize (diagnose), predict, and explain (treat) COVID-19 infections, and help manage socio-economic impacts. It also discusses primary warnings and alerts; tracking and prediction; data dashboards; diagnosis and prognosis; treatments and cures; and social control by the use of intelligent data analysis. It provides analysis reports, solutions using real-time data, and solution through web applications details.
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Intelligent Technologies and Robotics (SpringerNature-42732)
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EB RA644.C67 I48 2021
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