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Predictive models for COVID-19 detection using routine blood tests and machine learning.
Kistenev, Yury V; Vrazhnov, Denis A; Shnaider, Ekaterina E; Zuhayri, Hala.
  • Kistenev YV; Laboratory of Laser Molecular Imaging and Machine Learning, Tomsk State University, 36 Lenin Av., 634050 Tomsk, Russia.
  • Vrazhnov DA; Laboratory of Laser Molecular Imaging and Machine Learning, Tomsk State University, 36 Lenin Av., 634050 Tomsk, Russia.
  • Shnaider EE; Laboratory of Laser Molecular Imaging and Machine Learning, Tomsk State University, 36 Lenin Av., 634050 Tomsk, Russia.
  • Zuhayri H; Laboratory of Laser Molecular Imaging and Machine Learning, Tomsk State University, 36 Lenin Av., 634050 Tomsk, Russia.
Heliyon ; 8(10): e11185, 2022 Oct.
Article in English | MEDLINE | ID: covidwho-2082561
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.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Language: English Journal: Heliyon Year: 2022 Document Type: Article Affiliation country: J.heliyon.2022.e11185

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Language: English Journal: Heliyon Year: 2022 Document Type: Article Affiliation country: J.heliyon.2022.e11185