Predictive models for COVID-19 detection using routine blood tests and machine learning

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Predictive models for COVID-19 detection using routine blood tests and machine learning	922 KB	Adobe Acrobat PDF	Read	Download
DOI Доступ к ресурсу на сайте издателя			10.1016/j.heliyon.2022.e11185

Title: Predictive models for COVID-19 detection using routine blood tests and machine learning
Creator: Kistenev, Yury V.
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Vrazhnov, Denis A.
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Shnaider, Ekaterina E.
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Zuhayri, Hala
Date: 2022
DOI: 10.1016/j.heliyon.2022.e11185
Description: The problem of accurate, fast, and inexpensive COVID-19 tests has been urgent till now. Standard COVID-19 tests need high-cost reagents and specialized laboratories with high safety requirements, are time-consuming. Data of routine blood tests as a base of SARS-CoV-2 invasion detection allows using the most practical medicine facilities. But blood tests give general information about a patient’s state, which is not directly associated with COVID-19. COVID-19-specific features should be selected from the list of standard blood characteristics, and decision-making software based on appropriate clinical data should be created. This review describes the abilities to develop predictive models for COVID-19 detection using routine blood tests and machine learning.