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Internet of medical things for smart...

Chakraborty, Chinmay.

Internet of medical things for smart healthcareCovid-19 pandemic /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Internet of medical things for smart healthcareedited by Chinmay Chakraborty ... [et al.].
Reminder of title:	Covid-19 pandemic /
other author:	Chakraborty, Chinmay.
Published:	Singapore :Springer Singapore :2020.
Description:	xii, 305 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Medical informatics.
Online resource:	https://doi.org/10.1007/978-981-15-8097-0
ISBN:	9789811580970$q(electronic bk.)

Internet of medical things for smart healthcareCovid-19 pandemic /
Internet of medical things for smart healthcareCovid-19 pandemic /[electronic resource] :edited by Chinmay Chakraborty ... [et al.]. - Singapore :Springer Singapore :2020. - xii, 305 p. :ill., digital ;24 cm. - Studies in big data,v.802197-6503 ;. - Studies in big data ;v.1..

Chapter 1. Transmission Dynamics and Estimation of Basic Reproduction Number (R0) from Early Outbreak of Novel Coronavirus (COVID-19) in India -- Chapter 2. Covid -19 analysed by using machine deep learning -- Chapter 3. MML Classification Techniques for the pathogen based on pnuemonia-nCOVID-19 and the Detection of closely related lung diseases using Efficacious Learning Algorithms -- Chapter 4. Diagnosing COVID-19 Lung Inflammation using Machine Learning Algorithms: A Comparative Study -- Chapter 5. Factors Affecting the Success of Internet of Things for Enhancing Quality and Efficiency Implementation in Hospitals Sector in Jordan during the crises of Covid-19 -- Chapter 6. IoMT based Smart Diagnostic/Therapeutic Kit for Pandemic Patients -- Chapter 7. The Prediction Analysis of Covid-19 Cases using ARIMA and KALMAN Filter Models: A Case of Comparative Study -- Chapter 8. Exploration of cough recognition technologies grounded on sensors and artificial intelligence -- Chapter 9. A Review on use of Data Science for visualisation and prediction of the COVID-19 Pandemic and Early diagnosis of COVID-19 using Machine learning models -- Chapter 10. Fuzzy Cellular Automata Model For Discrete Dynamical System Representing Spread ofMERS And COVID-19 Virus, SumitaBasu and Sreeya Ghosh.

This book covers COVID-19 related research works and focuses on recent advances in the Internet of Things (IoT) in smart healthcare technologies. It includes reviews and original works on COVID-19 in terms of e-healthcare, medicine technology, life support systems, fast detection, diagnoses, developed technologies and innovative solutions, bioinformatics, datasets, apps for diagnosis, solutions for monitoring and control of the spread of COVID-19, among other topics. The book covers comprehensive studies from bioelectronics and biomedical engineering, artificial intelligence, and big data with a prime focus on COVID-19 pandemic.

ISBN: 9789811580970$q(electronic bk.)

Standard No.: 10.1007/978-981-15-8097-0doiSubjects--Topical Terms:

196487
Medical informatics.

LC Class. No.: Q342 / .I58 2020

Dewey Class. No.: 610.285

Internet of medical things for smart healthcareCovid-19 pandemic /
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505 0 $a Chapter 1. Transmission Dynamics and Estimation of Basic Reproduction Number (R0) from Early Outbreak of Novel Coronavirus (COVID-19) in India -- Chapter 2. Covid -19 analysed by using machine deep learning -- Chapter 3. MML Classification Techniques for the pathogen based on pnuemonia-nCOVID-19 and the Detection of closely related lung diseases using Efficacious Learning Algorithms -- Chapter 4. Diagnosing COVID-19 Lung Inflammation using Machine Learning Algorithms: A Comparative Study -- Chapter 5. Factors Affecting the Success of Internet of Things for Enhancing Quality and Efficiency Implementation in Hospitals Sector in Jordan during the crises of Covid-19 -- Chapter 6. IoMT based Smart Diagnostic/Therapeutic Kit for Pandemic Patients -- Chapter 7. The Prediction Analysis of Covid-19 Cases using ARIMA and KALMAN Filter Models: A Case of Comparative Study -- Chapter 8. Exploration of cough recognition technologies grounded on sensors and artificial intelligence -- Chapter 9. A Review on use of Data Science for visualisation and prediction of the COVID-19 Pandemic and Early diagnosis of COVID-19 using Machine learning models -- Chapter 10. Fuzzy Cellular Automata Model For Discrete Dynamical System Representing Spread ofMERS And COVID-19 Virus, SumitaBasu and Sreeya Ghosh.
520 $a This book covers COVID-19 related research works and focuses on recent advances in the Internet of Things (IoT) in smart healthcare technologies. It includes reviews and original works on COVID-19 in terms of e-healthcare, medicine technology, life support systems, fast detection, diagnoses, developed technologies and innovative solutions, bioinformatics, datasets, apps for diagnosis, solutions for monitoring and control of the spread of COVID-19, among other topics. The book covers comprehensive studies from bioelectronics and biomedical engineering, artificial intelligence, and big data with a prime focus on COVID-19 pandemic.
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