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Machine learning models to determine the risk of death or intubation

Grant number: unknown

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Key facts

  • Disease

    COVID-19

  • Start & end year

    N/A

  • Known Financial Commitments (USD)

    $0

  • Funder

    BBVA Foundation (Spain)

  • Principal Investigator

    Professor Concha Bielza

  • Research Location

    Spain

  • Lead Research Institution

    Artificial Intelligence Department of the Polytechnic University of Madrid

  • Research Priority Alignment

    N/A

  • Research Category

    Clinical characterisation and management

  • Research Subcategory

    Prognostic factors for disease severity

  • Special Interest Tags

    Data Management and Data Sharing

  • Study Type

    Unspecified

  • Clinical Trial Details

    N/A

  • Broad Policy Alignment

    Pending

  • Age Group

    Unspecified

  • Vulnerable Population

    Unspecified

  • Occupations of Interest

    Unspecified

Abstract

Based on data from more than 9,000 patients treated for the SARS-CoV-2 coronavirus in the Madrid hospitals of Ramón y Cajal, Fundación Jiménez Díaz and La Zarzuela, this work will develop machine learning models to predict the risk of death or of being intubated that a person has by analyzing the factors that will determine the prognosis. In addition, it will evaluate the efficiency of a treatment from comparisons of patients who have been treated with one drug or another and the relationship with the death rate. As the last objective, a Bayesian network model will be built that captures all the relationships between various variables -both clinical, as well as treatments and results- to make probabilistic reasoning about the risk of mortality, the success or not of a treatment and the why. This model will also be left open on a web platform for the entire scientific community.