Is It Possible to Distinguish COVID-19 Cases and Influenza with Wearable Devices? Analysis with Machine Learning

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F22%3APU144388" target="_blank" >RIV/00216305:26220/22:PU144388 - isvavai.cz</a>
Result on the web
<a href="http://www.jait.us/index.php?m=content&c=index&a=show&catid=217&id=1225" target="_blank" >http://www.jait.us/index.php?m=content&c=index&a=show&catid=217&id=1225</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.12720/jait.13.3.265-270" target="_blank" >10.12720/jait.13.3.265-270</a>

Result language
angličtina
Original language name
Is It Possible to Distinguish COVID-19 Cases and Influenza with Wearable Devices? Analysis with Machine Learning
Original language description
The COVID-19 situation is enforcing the creation of the diagnosis and supporting methods for early detection, which could serve as screening tools. In this paper, we introduced the methodologies based on wearable devices and machine learning, which distinguishes between COVID-19 disease and two types of Influenza. We checked the results of binary classification for various scenarios and multiclass classification. The results were evaluated separately for the cases before the pandemic and in the middle of the pandemic. In the middle of the pandemic, the best classification accuracy was achieved when distinguishing between COVID-19 and Influenza cases with k-NN (the balanced accuracy was equal to 73%). The highest sensitivity was achieved for Logistic Regression - 61%. The successful distinction between Influenza types was achieved in 80 % for XGBoost and Decision Tree. Additionally, the balanced accuracy for multiclass classification was equal to 69 % for k-NN.
Czech name
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Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
20601 - Medical engineering

Project
<a href="/en/project/VI04000039" target="_blank" >VI04000039: Early COVID-19 infection detection system for the safety of vulnerable groups using artificial intelligence</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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