Role Of Information Technology for Successful Responses to Covid-19 Pandemic

Manalu, Erwin P.S.; Muditomo, Arianto; Adriana, Dadi; Trisnowati, Yanuar; P, Zulfikar Kesuma; H, Rini Dwiyani

doi:10.1109/icimtech50083.2020.9211290

Cited by 20 publications

(13 citation statements)

References 11 publications

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“…The platform increases accessibility to the proper dataset (81) the treatment and research process. ML is one of the new technologies for tracking the spread of the virus and finding effective parameters in it.…”

Section: Applications Are Vulnerable To Coronavirus Attacksmentioning

confidence: 99%

A Survey on Machine Learning and Internet of Medical Things-Based Approaches for Handling COVID-19: Meta-Analysis

Band

Ardabili

Yarahmadi

et al. 2022

Front. Public Health

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Early diagnosis, prioritization, screening, clustering, and tracking of patients with COVID-19, and production of drugs and vaccines are some of the applications that have made it necessary to use a new style of technology to involve, manage, and deal with this epidemic. Strategies backed by artificial intelligence (A.I.) and the Internet of Things (IoT) have been undeniably effective to understand how the virus works and prevent it from spreading. Accordingly, the main aim of this survey is to critically review the ML, IoT, and the integration of IoT and ML-based techniques in the applications related to COVID-19, from the diagnosis of the disease to the prediction of its outbreak. According to the main findings, IoT provided a prompt and efficient approach to tracking the disease spread. On the other hand, most of the studies developed by ML-based techniques aimed at the detection and handling of challenges associated with the COVID-19 pandemic. Among different approaches, Convolutional Neural Network (CNN), Support Vector Machine, Genetic CNN, and pre-trained CNN, followed by ResNet have demonstrated the best performances compared to other methods.

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Section: Applications Are Vulnerable To Coronavirus Attacksmentioning

confidence: 99%

A Survey on Machine Learning and Internet of Medical Things-Based Approaches for Handling COVID-19: Meta-Analysis

Band

Ardabili

Yarahmadi

et al. 2022

Front. Public Health

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show abstract

“…The platform increases accessibility to the proper dataset [70] According to Table 8, most of these studies lack numerical analysis for the method performance. One of the main reasons can be the nature of IoT technique which goes through a practical process and shows its performance in practical applications and does not need to provide numerical statistics.…”

Section: 𝐶𝑜𝑟𝑟𝑒𝑙𝑎𝑡𝑖𝑜𝑛 𝐶𝑜𝑒𝑓𝑓𝑖𝑐𝑖𝑒𝑛𝑡 = 𝐶𝑜𝑣(𝑥 𝑥 ̂) 𝜎 𝑥 𝜎 𝑥 ̂mentioning

confidence: 99%

Machine Learning and Internet of Medical Things for Handling COVID-19: Meta-Analysis

Band¹,

Ardabili²,

Yarahmadi³

et al. 2022

Preprint

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Early diagnosis, prioritization, screening, clustering and tracking of COVID-19 patients, and production of drugs and vaccines are some of the applications that have made it necessary to use a new style of technology to involve, to manage and deal with this epidemic. Strategies backed by artificial intelligence (AI) and the Internet of Things (IoT) have been undeniable to understand how the virus works and try to prevent it from spreading. Accordingly, the main aim of this survey article is to highlight the methods of ML, IoT and the integration of IoT and ML-based techniques in the applications related to COVID-19 from the diagnosis of the disease to the prediction of its outbreak. According to the main findings, IoT provided a prompt and efficient approach of following the disease spread. Most of the studies developed by ML-based techniques for handling COVID-19 based dataset provided performance criteria. The most popular performance criteria, is related to accuracy factor. It can be employed for comparing the ML-based methods with different datasets. According to the results, CNN with SVM classifier, Genetic CNN and pre-trained CNN followed by ResNet, provided highest accuracy values. On the other hand, the lowest accuracy was related to single CNN followed by XGboost and KNN methods.

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“…The wide use of these technologies among all the industries has also been witnessed during this period. The famous industries that adopted the emerging technologies in supply chain operations and business models include the pharmaceutical industry, Agri-food industry, manufacturing, service industry, electronic industry, and construction industry (Dilyard et al, 2020;Manalu et al, 2020;Salah et al, 2020). The adoption and implementation of emerging technologies in these industries provide substantial support to combat the pandemic effects.…”

Section: Ro2 Sectors Where Emerging Technologies Were Implementedmentioning

confidence: 99%

Application and Impact of New Technologies in the Supply Chain Management During COVID-19 Pandemic: A Systematic Literature Review

Muhammad¹,

Manzoor²

2021

IJEBA

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Purpose:The purpose of this study is to examine the application of emerging technologies during the COVID-19 pandemic and their impact on supply chain management. Design/Methodology/approach: A systematic literature review was conducted to identify the application and impact of new technologies on supply chain management. Findings: The findings revealed that blockchain technology, IoT, artificial intelligence, big data analytics, cloud computing, 5G and smartphone application, and the use of robots and drones are the key technologies used during COVID-19 in supply chain management, and they showed a substantial impact on the supply chain resilience, agility, and adaptability. Key barriers include higher investment costs, lack of government regulations and support, and deficiency of skilled and technical human resources faced during these technologies' implementation.Practical Implications: This study evaluated the systematic review through the google scholar search engine and only adopted peer-reviewed scholarly journals, conference proceedings, and opinion papers. The study provides valuable insight to supply chain officials, policymakers, and governments. The emerging technologies have the crucial potential to resolve the supply chain disruptions, if they are addressed seriously. Originality/ value: This study provides social implications by providing insight regarding the improved standards of living. This study is the first to address emerging technologies in supply chain management during

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Role Of Information Technology for Successful Responses to Covid-19 Pandemic

Cited by 20 publications

References 11 publications

A Survey on Machine Learning and Internet of Medical Things-Based Approaches for Handling COVID-19: Meta-Analysis

A Survey on Machine Learning and Internet of Medical Things-Based Approaches for Handling COVID-19: Meta-Analysis

Machine Learning and Internet of Medical Things for Handling COVID-19: Meta-Analysis

Application and Impact of New Technologies in the Supply Chain Management During COVID-19 Pandemic: A Systematic Literature Review

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