Use of artificial intelligence to assess genetic predisposition to develop critical COVID-19 disease: a comparative study of machine learning models.

Journal: Advances in laboratory medicine
Published Date: May 5, 2025

Abstract

OBJECTIVES: Early prediction of critical COVID-19 disease is crucial for an optimal clinical management. The objective of this study was to optimize predictive models for critical COVID-19 disease. Clinical data, laboratory data and genetic polymorphisms were integrated into AI models to compare the performance of different machine learning algorithms.

Authors

  • Salomon Martin Perez
    Laboratory Medicine Department, Virgen Macarena University Hospital, Seville, Spain.
  • Flora Sanchez Jimenez
    Service of Clinical Biochemistry Virgen Macarena University Hospital Seville, Seville, Spain.
  • Sandra Fuentes Cantero
    Department of Clinical Laboratory Chemistry Rio Tinto General Hospital Huelva, Huelva, Spain.
  • Marta Jímenez Barragan
    Service of Clinical Biochemistry Virgen Macarena University Hospital Seville, Seville, Spain.
  • Catalina Sanchez Mora
    Service of Clinical Biochemistry Virgen Macarena University Hospital Seville, Seville, Spain.
  • Juan M Borreguero Leon
    Service of Clinical Biochemistry Virgen Macarena University Hospital Seville, Seville, Spain.
  • Arrobas Velilla Teresa
    Service of Clinical Biochemistry Virgen Macarena University Hospital Seville, Seville, Spain.
  • Agustín Valido Morales
    Unit of Pulmonology, Virgen Macarena University Hospital Seville, Seville, Spain.
  • Juan A Delgado Torralbo
    Unit of Pulmonology, Virgen Macarena University Hospital Seville, Seville, Spain.
  • Antonio León Justel
    Service of Clinical Biochemistry Virgen Macarena University Hospital Seville, Seville, Spain.

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