國立高雄大學圖資館 |

Language: English

Back

Intelligent data analysis for COVID-...

Bhattacharyya, Siddhartha.

Intelligent data analysis for COVID-19 pandemic

Record Type:	Electronic resources : Monograph/item
Title/Author:	Intelligent data analysis for COVID-19 pandemicedited 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.
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$q(electronic bk.)

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$q(electronic bk.)

Standard No.: 10.1007/978-981-16-1574-0doiSubjects--Topical Terms:

894680
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
LDR:03633nmm a2200337 a 4500 001 602394
003 DE-He213
005 20210626200705.0
006 m d
007 cr nn 008maaau
008 211112s2021 si s 0 eng d
020 $a 9789811615740$q(electronic bk.)
020 $a 9789811615733$q(paper)
024 7 $a 10.1007/978-981-16-1574-0 $2 doi
035 $a 978-981-16-1574-0
040 $a GP $c GP
041 0 $a eng
050 4 $a RA644.C67 $b I48 2021
072 7 $a UYQ $2 bicssc
072 7 $a TEC009000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 362.1962414 $2 23
090 $a RA644.C67 $b I61 2021
245 0 0 $a Intelligent data analysis for COVID-19 pandemic $h [electronic resource] / $c edited by M. Niranjanamurthy, Siddhartha Bhattacharyya, Neeraj Kumar.
260 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2021.
300 $a xix, 370 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Algorithms for intelligent systems, $x 2524-7565
505 0 $a 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.
520 $a 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.
650 0 $a COVID-19 Pandemic, 2020- $x Data processing. $3 894680
650 1 4 $a Computational Intelligence. $3 338479
650 2 4 $a Artificial Intelligence. $3 212515
650 2 4 $a Statistics, general. $3 275684
650 2 4 $a Health Informatics. $3 274212
700 1 $a Niranjanamurthy, M. $3 898066
700 1 $a Bhattacharyya, Siddhartha. $3 736923
700 1 $a Kumar, Neeraj. $3 865640
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer Nature eBook
830 0 $a Algorithms for intelligent systems. $3 857955
856 4 0 $u https://doi.org/10.1007/978-981-16-1574-0
950 $a Intelligent Technologies and Robotics (SpringerNature-42732)