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Risk Group Determination in Case of COVID-19 Infection

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Bioengineering and Biomedical Signal and Image Processing (BIOMESIP 2021)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 12940))

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Abstract

The possibility of quick decoding of individual human genome has allowed us to amass vast data arrays of diseases, as well as associated human DNA mutations. It is well-known that DNA mutations cause genetic diseases and disorders. Among the risk group of severe coronavirus disease cases are patients with preexisting cardiovascular or respiratory diseases, oncologic pathologies, hypertension, and other disorders. Coronavirus disease severity can be predicted using machine learning methods trained on features corresponding to single nucleotide polymorphisms in gene coding sequences of patient genomes.

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Author information

Authors and Affiliations

  1. V. M. Glushkov Institute of Cybernetics, Kyiv, 03187, Ukraine

    Borys Biletskyy & Anatoliy Gupal

Authors
  1. Borys Biletskyy
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  2. Anatoliy Gupal
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Corresponding author

Correspondence to Borys Biletskyy .

Editor information

Editors and Affiliations

  1. University of Granada, Granada, Spain

    Ignacio Rojas

  2. University of Granada, Granada, Spain

    Daniel Castillo-Secilla

  3. University of Granada, Granada, Spain

    Luis Javier Herrera

  4. Universidad de Granada, Granada, Granada, Spain

    Héctor Pomares

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Biletskyy, B., Gupal, A. (2021). Risk Group Determination in Case of COVID-19 Infection. In: Rojas, I., Castillo-Secilla, D., Herrera, L.J., Pomares, H. (eds) Bioengineering and Biomedical Signal and Image Processing. BIOMESIP 2021. Lecture Notes in Computer Science(), vol 12940. Springer, Cham. https://doi.org/10.1007/978-3-030-88163-4_36

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  • DOI: https://doi.org/10.1007/978-3-030-88163-4_36

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-88162-7

  • Online ISBN: 978-3-030-88163-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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