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The Science behind the COVID Pandemic and Healthcare Technology Solutions

Overview of attention for book
The Science behind the COVID Pandemic and Healthcare Technology Solutions
Springer International Publishing

Table of Contents

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    Book Overview
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    Chapter 1 The Science behind the COVID Pandemic and Healthcare Technology Solutions: An Introduction
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    Chapter 2 Pandemic’s Behavior of One Year in Six Most Affected Countries Using Polynomial Generated SIR Model
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    Chapter 3 Digital Contact Tracing for COVID 19: A Missed Opportunity or an Expensive Mess
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    Chapter 4 A Re-configurable Software-Hardware CNN Framework for Automatic Detection of Respiratory Symptoms
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    Chapter 5 A Comprehensive Telemedicine Service in Hong Kong Provided Through a Mobile Application
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    Chapter 6 Adapting to Live in the Global Pandemic Era: Case Studies
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    Chapter 7 Towards QR Code Health Systems Amid COVID-19: Lessons Learnt from Other QR Code Digital Technologies
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    Chapter 8 Optimal Testing Strategies for Infectious Diseases
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    Chapter 9 Contact Tracing for Healthcare Facilities Using Bluetooth
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    Chapter 10 Monitoring the Health and Movement of Quarantined COVID-19 Patients with Wearable Devices
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    Chapter 11 Context-Aware and User Adaptive Smart Home Ecosystems Using Wearable and Semantic Technologies During and Post COVID-19 Pandemic
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    Chapter 12 Wearable Tracking: An Effective Smartwatch Approach in Distributed Population Tracking During Pandemics
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    Chapter 13 Making the Invisible Visible: A Science and Society View of Developing Non-invasive Thermal Technology
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    Chapter 14 EMD and Horizontal Visibility Graph Based Disease Tagging for Covid-Positive Chest Radiographs
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    Chapter 15 Mobility Analytics and COVID-19 in Greece
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    Chapter 16 Dynamical Modeling of Outbreak and Control of Pandemics: Assessing the Resilience of Healthcare Infrastructure Under Mitigation Policies
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    Chapter 17 COVID-19 Diagnosis with Artificial Intelligence
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    Chapter 18 COVID-19 Features Detection Using Machine Learning Models and Classifiers
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    Chapter 19 Cough Detection Using Mobile Phone Accelerometer and Machine Learning Techniques
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    Chapter 20 Mental Healthcare in the ‘New Normal’: Digital Technologies for Pandemics
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    Chapter 21 Innovations in Surgery—How Advances in the Delivery of Surgical Care and Training Can Help Hospitals Recover from COVID-19
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    Chapter 22 A Biomarker-Based Model to Assist the Identification of Stress in Health Workers Involved in Coping with COVID-19
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    Chapter 23 The Experience of Diagnosis and Management of Oral Maxillofacial Surgery, and Dental Education During the Pandemic
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    Chapter 24 Digitizing Pandemic Response Operations: The Experiences from a Small Island Nation
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    Chapter 25 Resilience to COVID-19 Pandemic
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    Chapter 26 Use of Remote Sensing and GIS Techniques for Adaptation and Mitigation of COVID-19 Pandemic
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    Chapter 27 Mapping Blockchain Technology Prospects and Solutions in the Healthcare Industry for Pandemic Crises
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    Chapter 28 The Role of Healthcare in Post Pandemic Era—“COVID Normal”
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    Chapter 29 Scenario Assessment for COVID-19 Outbreak in Iran: A Hybrid Simulation–Optimization Model for Healthcare Capacity Allocation
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    Chapter 30 Ensuring a Superior Level of Prepareness and Readiness by Adopting a Knowledge-Based Network-Centric Approach Leveraging Information Systems for Emergency and Disaster Management
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    Chapter 31 mHealth Systems and Applications in Post-pandemic Healthcare
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    Chapter 32 Synergistic Effects of Environmental Factors on the Spread of Corona Virus
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    Chapter 33 CFD Analysis of COVID-19 Dispersion via Speaking, Breathing, Coughing, and (or) Sneezing
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    Chapter 34 COVID-19 Pandemic: Lessons Learned and Roadmap for the Future
Attention for Chapter 19: Cough Detection Using Mobile Phone Accelerometer and Machine Learning Techniques
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Chapter title
Cough Detection Using Mobile Phone Accelerometer and Machine Learning Techniques
Chapter number 19
Book title
The Science behind the COVID Pandemic and Healthcare Technology Solutions
Published by
Springer, Cham, January 2022
DOI 10.1007/978-3-031-10031-4_19
Book ISBNs
978-3-03-110030-7, 978-3-03-110031-4
Authors

Ali, Shan E., Khan, Ali Nawaz, Zia, Shafaq

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 2 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 2 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 50%
Unknown 1 50%
Readers by discipline Count As %
Veterinary Science and Veterinary Medicine 1 50%
Unknown 1 50%

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