Machine learning algorithms to predict outcomes in children and adolescents with COVID-19: A systematic review.

Journal: Artificial intelligence in medicine
Published Date: Feb 24, 2024

Abstract

BACKGROUND AND OBJECTIVES: We aimed to analyze the study designs, modeling approaches, and performance evaluation metrics in studies using machine learning techniques to develop clinical prediction models for children and adolescents with COVID-19.

Authors

  • Adriano Lages Dos Santos
    Department of Pediatrics, Health Sciences Postgraduate Program, School of Medicine, Federal University of Minas Gerais (UFMG), Belo Horizonte, Brazil; Federal Institute of Education, Science and Technology of Minas Gerais (IFMG), Belo Horizonte, Brazil. Electronic address: adriano.santos@ifmg.edu.br.
  • Clara Pinhati
    Department of Pediatrics, Health Sciences Postgraduate Program, School of Medicine, Federal University of Minas Gerais (UFMG), Belo Horizonte, Brazil.
  • Jonathan Perdigão
    Department of Pediatrics, Health Sciences Postgraduate Program, School of Medicine, Federal University of Minas Gerais (UFMG), Belo Horizonte, Brazil.
  • Stella Galante
    Department of Pediatrics, Health Sciences Postgraduate Program, School of Medicine, Federal University of Minas Gerais (UFMG), Belo Horizonte, Brazil.
  • Ludmilla Silva
    Department of Pediatrics, Health Sciences Postgraduate Program, School of Medicine, Federal University of Minas Gerais (UFMG), Belo Horizonte, Brazil.
  • Isadora Veloso
    Department of Pediatrics, Health Sciences Postgraduate Program, School of Medicine, Federal University of Minas Gerais (UFMG), Belo Horizonte, Brazil.
  • Ana Cristina Simões E Silva
    Interdisciplinary Medical Research Laboratory, Faculty of Medicine, Federal University of Minas Gerais, Belo Horizonte, MG, Brazil.
  • Eduardo Araújo Oliveira
    Department of Pediatrics, Health Sciences Postgraduate Program, School of Medicine, Federal University of Minas Gerais (UFMG), Belo Horizonte, Brazil.

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