Machine learning and artificial intelligence within pediatric autoimmune diseases: applications, challenges, future perspective.

Journal: Expert review of clinical immunology
Published Date: Jun 14, 2024

Abstract

INTRODUCTION: Autoimmune disorders affect 4.5% to 9.4% of children, significantly reducing their quality of life. The diagnosis and prognosis of autoimmune diseases are uncertain because of the variety of onset and development. Machine learning can identify clinically relevant patterns from vast amounts of data. Hence, its introduction has been beneficial in the diagnosis and management of patients.

Authors

  • Parniyan Sadeghi
    Network of Interdisciplinarity in Neonates and Infants (NINI), Universal Scientific Education and Research Network (USERN), Tehran, Iran.
  • Hanie Karimi
    Network of Interdisciplinarity in Neonates and Infants (NINI), Universal Scientific Education and Research Network (USERN), Tehran, Iran.
  • Atiye Lavafian
    Network of Interdisciplinarity in Neonates and Infants (NINI), Universal Scientific Education and Research Network (USERN), Tehran, Iran.
  • Ronak Rashedi
    Network of Interdisciplinarity in Neonates and Infants (NINI), Universal Scientific Education and Research Network (USERN), Tehran, Iran.
  • Noosha Samieefar
    Network of Interdisciplinarity in Neonates and Infants (NINI), Universal Scientific Education and Research Network (USERN), Tehran, Iran.
  • Sajad Shafiekhani
    Department of Biomedical Engineering, Buein Zahra Technical University, Qazvin, Iran.
  • Nima Rezaei
    a Research Center for Immunodeficiencies , Children's Medical Center, Tehran University of Medical Sciences , Tehran , Iran.

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