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

Yury V Kistenev; Denis A Vrazhnov; Ekaterina E Shnaider; Hala Zuhayri

doi:10.1016/j.heliyon.2022.e11185

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

Heliyon. 2022 Oct;8(10):e11185. doi: 10.1016/j.heliyon.2022.e11185. Epub 2022 Oct 22.

Authors

Yury V Kistenev¹, Denis A Vrazhnov¹, Ekaterina E Shnaider¹, Hala Zuhayri¹

Affiliation

¹ Laboratory of Laser Molecular Imaging and Machine Learning, Tomsk State University, 36 Lenin Av., 634050 Tomsk, Russia.

Abstract

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.

Keywords: Blood tests; COVID-19; Machine learning.

Publication types

Review