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- W4307150871 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." @default.
- W4307150871 created "2022-10-28" @default.
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- W4307150871 date "2022-10-01" @default.
- W4307150871 modified "2023-09-26" @default.
- W4307150871 title "Predictive models for COVID-19 detection using routine blood tests and machine learning" @default.
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- W4307150871 doi "https://doi.org/10.1016/j.heliyon.2022.e11185" @default.
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