
- Publisher's listprice EUR 192.59
-
The price is estimated because at the time of ordering we do not know what conversion rates will apply to HUF / product currency when the book arrives. In case HUF is weaker, the price increases slightly, in case HUF is stronger, the price goes lower slightly.
- Discount 8% (cc. 6 536 Ft off)
- Discounted price 75 161 Ft (71 582 Ft + 5% VAT)
81 696 Ft
Availability
Estimated delivery time: In stock at the publisher, but not at Prospero's office. Delivery time approx. 3-5 weeks.
Not in stock at Prospero.
Why don't you give exact delivery time?
Delivery time is estimated on our previous experiences. We give estimations only, because we order from outside Hungary, and the delivery time mainly depends on how quickly the publisher supplies the book. Faster or slower deliveries both happen, but we do our best to supply as quickly as possible.
Product details:
- Edition number 1st ed. 2020
- Publisher Springer
- Date of Publication 11 November 2021
- Number of Volumes 1 pieces, Book
- ISBN 9789811580994
- Binding Paperback
- No. of pages305 pages
- Size 235x155 mm
- Weight 492 g
- Language English
- Illustrations 23 Illustrations, black & white; 177 Illustrations, color 270
Categories
Short description:
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.
Long description:
Table of Contents:
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.
More