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

被引：12

作者：

Kistenev, Yury V. ^{[1
]}

Vrazhnov, Denis A. ^{[1
]}

Shnaider, Ekaterina E. ^{[1
]}

Zuhayri, Hala ^{[1
]}

机构：

[1] Tomsk State Univ, Lab Laser Mol Imaging & Machine Learning, 36 Lenin Ave, Tomsk 634050, Russia

来源：

HELIYON | 2022年 / 8卷 / 10期

关键词：

COVID-19; Blood tests; Machine learning;

D O I：

10.1016/j.heliyon.2022.e11185

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

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.

引用

页数：11

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