Exploratory Data Analysis, Classification, Comparative Analysis, Case Severity Detection, and Internet of Things in COVID 19 Telemonitoring for Smart Hospitals

Journal article


Shabbir, A., Shabbir, M., Javed, A. R., Rizwan, M., Iwendi, C. and Chakraborty, C. 2022. Exploratory Data Analysis, Classification, Comparative Analysis, Case Severity Detection, and Internet of Things in COVID 19 Telemonitoring for Smart Hospitals. Journal of Experimental & Theoretical Artificial Intelligence. 35 (4), pp. 507-534. https://doi.org/10.1080/0952813X.2021.1960634
AuthorsShabbir, A., Shabbir, M., Javed, A. R., Rizwan, M., Iwendi, C. and Chakraborty, C.
Abstract

The proportion of COVID-19 patients is significantly expanding around the world. Treatment with serious consideration has become a significant problem. Identifying clinical indicators of succession towards severe conditions is desperately required to empower hazard stratification and optimise resource allocation in the pandemic of COVID-19. Consequently, the classification of severity level is significant for the patient’s triaging. It is required to categorise the severity level as mild, moderate, severe, and critical based on the patients’ symptoms. Various symptomatic parameters may encourage the evaluation of infection seriousness. Likewise, with the rapid spread and transmissibility of COVID-19 patients, it is crucial to utilise telemonitoring schemes for COVID-19 patients. Telemonitoring mediation encourages remote data and information exchange among medicinal services, suppliers, and patients, furthermore, risk mitigation and provision of appropriate medical facilities. This paper provides explorative data analysis of symptoms, comorbidities, and other parameters, comparing different machine learning algorithms for case severity detection. This paper also provides a system (based on the degree of truthfulness) for case severity detection that might be utilised to stratify risk levels for anticipated moderate and severe COVID-19 patients. Finally, we provide a telemonitoring model of COVID-19 patients to ensure the remote and continuous monitoring of case severity progression and appropriate risk mitigation strategies.

KeywordsCOVID-19; exploratory data analysis; internet of things (iot); severity detection; classification; telemonitoring
Year2022
JournalJournal of Experimental & Theoretical Artificial Intelligence
Journal citation35 (4), pp. 507-534
PublisherTaylor & Francis (Routledge)
ISSN1362-3079
Digital Object Identifier (DOI)https://doi.org/10.1080/0952813X.2021.1960634
Web address (URL)https://www.tandfonline.com/doi/abs/10.1080/0952813X.2021.1960634
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All rights reserved
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Restricted
Output statusPublished
Publication dates
Online09 Feb 2022
Publication process dates
Accepted01 Jan 2022
Deposited27 Mar 2024
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Controlled
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https://repository.derby.ac.uk/item/q566y/exploratory-data-analysis-classification-comparative-analysis-case-severity-detection-and-internet-of-things-in-covid-19-telemonitoring-for-smart-hospitals

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