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Open AccessJournal ArticleDOI

Blockchain and AI-Based Solutions to Combat Coronavirus (COVID-19)-Like Epidemics: A Survey

TLDR
An extensive survey on the use of blockchain andAI for combating coronavirus (COVID-19) epidemics based on the rapidly emerging literature and introduces a new conceptual architecture which integrates blockchain and AI specific for COVID- 19 fighting.
Abstract
The beginning of 2020 has seen the emergence of coronavirus outbreak caused by a novel virus called SARS-CoV-2. The sudden explosion and uncontrolled worldwide spread of COVID-19 show the limitations of existing healthcare systems in timely handling public health emergencies. In such contexts, innovative technologies such as blockchain and Artificial Intelligence (AI) have emerged as promising solutions for fighting coronavirus epidemic. In particular, blockchain can combat pandemics by enabling early detection of outbreaks, ensuring the ordering of medical data, and ensuring reliable medical supply chain during the outbreak tracing. Moreover, AI provides intelligent solutions for identifying symptoms caused by coronavirus for treatments and supporting drug manufacturing. Therefore, we present an extensive survey on the use of blockchain and AI for combating COVID-19 epidemics. First, we introduce a new conceptual architecture which integrates blockchain and AI for fighting COVID-19. Then, we survey the latest research efforts on the use of blockchain and AI for fighting COVID-19 in various applications. The newly emerging projects and use cases enabled by these technologies to deal with coronavirus pandemic are also presented. A case study is also provided using federated AI for COVID-19 detection. Finally, we point out challenges and future directions that motivate more research efforts to deal with future coronavirus-like epidemics.

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Journal ArticleDOI

6G Internet of Things: A Comprehensive Survey

TL;DR: In this paper, the authors explore the emerging opportunities brought by 6G technologies in IoT networks and applications, by conducting a holistic survey on the convergence of 6G and IoT, and highlight interesting research challenges and point out potential directions to spur further research in this promising area.
Journal ArticleDOI

COVID-19 open source data sets: a comprehensive survey

TL;DR: This survey is motivated by the open source efforts that can be mainly categorized as (a) COVID-19 diagnosis from CT scans, X-ray images, and cough sounds, (b) CO VID-19 case reporting, transmission estimation, and prognosis from epidemiological, demographic, and mobility data, (c) COvid-19 emotional and sentiment analysis from social media, and (d) knowledge-based discovery and semantic analysis from the collection of scholarly articles covering COVID.
Journal ArticleDOI

COVID-19 and hospitality 5.0: Redefining hospitality operations

TL;DR: In this article, the authors investigated the effects of past pandemics and epidemics on the global hospitality industry, and how the industry responded to them, and further explored the role of technology in ensuring hygiene and cleanliness.
Journal ArticleDOI

Supply chain disruption during the COVID-19 pandemic: Recognizing potential disruption management strategies

TL;DR: In this article , the authors present a set of up-to-date bibliometric, network, and thematic analyses to identify the influential contributors, main research streams, and disruption management strategies related to the SC performance under the COVID-19 settings.
Journal ArticleDOI

Federated Learning for Smart Healthcare: A Survey

TL;DR: A comprehensive survey on the use of federated learning in smart healthcare can be found in this paper , where the authors provide a state-of-the-art review on the emerging applications of FL in key healthcare domains, including health data management, remote health monitoring, medical imaging, and COVID-19 detection.
References
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Pattern Recognition and Machine Learning

TL;DR: Probability Distributions, linear models for Regression, Linear Models for Classification, Neural Networks, Graphical Models, Mixture Models and EM, Sampling Methods, Continuous Latent Variables, Sequential Data are studied.
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A pneumonia outbreak associated with a new coronavirus of probable bat origin

TL;DR: Identification and characterization of a new coronavirus (2019-nCoV), which caused an epidemic of acute respiratory syndrome in humans in Wuhan, China, and it is shown that this virus belongs to the species of SARSr-CoV, indicates that the virus is related to a bat coronav virus.
Journal ArticleDOI

Characteristics of and Important Lessons From the Coronavirus Disease 2019 (COVID-19) Outbreak in China: Summary of a Report of 72 314 Cases From the Chinese Center for Disease Control and Prevention

TL;DR: Hospitalised COVID-19 patients are frequently elderly subjects with co-morbidities receiving polypharmacy, all of which are known risk factors for d
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A survey on deep learning in medical image analysis

TL;DR: This paper reviews the major deep learning concepts pertinent to medical image analysis and summarizes over 300 contributions to the field, most of which appeared in the last year, to survey the use of deep learning for image classification, object detection, segmentation, registration, and other tasks.
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