UID:
almahu_9949598631902882
Format:
1 online resource.
ISBN:
9781003282020
,
1003282024
,
9781000572810
,
1000572811
,
9781000572773
,
1000572773
Content:
"The recent COVID-19 global pandemic exemplifies the need for efficient, reliable, and real-time tools and technology for forecasting and predicting healthcare disasters as well as for helping to restrict subsequent spread and fatality of deadly diseases. This new book discusses many of the innovative and state-of-the-art tools and technology that can help meet the challenges of predicting such disasters. The chapters offer a plethora of useful information for designing healthcare disaster management systems that can be dynamically configurable with implementation of today's modern technology, such as cloud computing, artificial intelligence, IoT, data analytics, and machine learning. These can increase effectiveness in remote sensing technologies, data analytics, data storage, communication networks, geographic information system (GIS), and global positioning System (GPS), to name a few. The book discusses mathematical models using graph-based approaches for analyzing dynamic, heterogeneous, and unstructured data for applications in epidemiology. The authors also address the use of mobile applications for communication efforts and remote monitoring for gauging health and the effectiveness of preventive healthcare measures. The chapters discuss influencing factors that directly or indirectly target public health infrastructure that can lead to or exacerbate global health crises, such as extreme climate changes, refugee health crises, terrorism and cyberterrorism, and technology-related incidents. The book further looks at efficient methods to analyze disasters and how to deliver healthcare in areas of conflict and crisis. This important volume, Global Healthcare Disasters: Predicting the Unpredictable with Emerging Technologies, provides a bounty of useful information for health professionals, academicians, researchers, governmental agencies, and policymakers across the world to predict, mitigate, and manage global health disaster with emerging technologies."--
Note:
Role of Knowledge Graphs in Analyzing Epidemics and Health Disasters / Sushmita Singh and Dr. Manvi Siwach -- Forecasting of COVID-19 with the ARIMA Model in India as a Preventive Measure of Healthcare Catastrophe / Sanjeev Kr. Jain and Kapil Mohan Garg -- Role of Artificial Intelligence in the Era of COVID-19 to Improve Hospital Management / Ruqaiya Khanam -- Challenges of Global Healthcare Disasters / Deepika Sherawat, Sonia, and Priyanka Shukla -- Healthcare Disaster Prediction with IoT, Data Analytics, and Machine Learning / Priyanka Shukla, Akanksha Sehgal, Sonia, and Deepika Sherawat -- Effectiveness of Aarogya Setu Mobile Application During COVID-19 Healthcare Management: A Technology Acceptance Model-Based Approach / Sarika Sharma and D. P. Goyal -- CoReS-Respiratory Strength Predicting Framework Using Noninvasive Technology for Remote Monitoring During Heath Disasters / Adarsh Garg -- Exploring the Scope of Policy Issues Influencing IoT Health and Big Data: A Structured Review / Anthony Maina and Upasana Singh -- COVID-19 Disaster Healthcare Management System in Rural Areas / Bhuvana M. and Vasantha S. -- Sentiment Analysis for Sustainable Healthcare During Pandemic Outbreak: Lessons Learned from COVID-19 / Archana Singh, Sarika Sharma, and Sandeep Sinha -- Design Schema to Offer Security and Confidentiality to Healthcare Data in Cloud Environment / N. Thillaiarasu, Raju Shanmugam, Thirunavukkarasu K., and Shahnawz Khan.
Additional Edition:
Print version: Global healthcare disasters. Palm Bay, FL, USA ; Burlington, ON, Canada : Apple Academic Press ; Boca Raton, FL, USA ; Abingdon, Oxon, UK : CRC Press, 2022 ISBN 1774910047
Additional Edition:
ISBN 9781774910047
Language:
English
DOI:
10.1201/9781003282020
URL:
https://www.taylorfrancis.com/books/9781003282020
