Chinmay Chakraborty,
Amit Banerjee,
Lalit Garg,
Joel J. P. C. Rodrigues
e.a.
Springer Nature Singapore
e druk, 2021
9789811580994
Internet of Medical Things for Smart Healthcare
Covid-19 Pandemic
Specificaties
Paperback, blz.
|
Engels
Springer Nature Singapore |
e druk, 2021
ISBN13: 9789811580994
Rubricering
Onderdeel van serie
Studies in Big Data
Verwachte levertijd ongeveer 9 werkdagen
Samenvatting
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.
Specificaties
ISBN13:9789811580994
Taal:Engels
Bindwijze:paperback
Uitgever:Springer Nature Singapore
Serie:Studies in Big Data
Inhoudsopgave
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.
