Predictive appendicitis scale for children under 4 years of age

Is it possible to apply artificial intelligence?

Authors

  • Dayhana Arango Cárdenas Estudiante
  • Jorge Andrés Castrillón Lozano Estudiante
  • Ximena Areiza Ocampo Estudiante

DOI:

https://doi.org/10.31053/1853.0605.v81.n1.44316

Keywords:

artificial intelligence, appendicitis, pediatric

Abstract

Acute appendicitis in the pediatric population is a pathology of heterogeneous presentation that is currently diagnosed using various criteria or predictive scales, which have proven not to be sufficiently accurate to be standardized, however, methods have been created to establish a more accurate diagnosis, an aspect that has been provided by artificial intelligence, which through different algorithms has the ability to show the patient's condition and the most appropriate intervention for this, thus reducing the rate of unnecessary interventions and therefore possible related complications.

Downloads

Download data is not yet available.

Author Biographies

  • Dayhana Arango Cárdenas, Estudiante
    1. Facultad de Medicina, Universidad Cooperativa de Colombia, Medellín, Colombia
  • Jorge Andrés Castrillón Lozano , Estudiante
    • Facultad de Medicina, Universidad Cooperativa de Colombia, Medellín, Colombia
    • Grupo de Investigación Infettare, Universidad Cooperativa de Colombia, Medellín, Colombia.
  • Ximena Areiza Ocampo , Estudiante
    1. Facultad de Medicina, Universidad Cooperativa de Colombia, Medellín, Colombia

References

1. Rassi R, Muse F, Cuestas E. Escala predictiva de apendicitis para menores de 4 años. Rev Fac Cien Med Univ Nac Cordoba. 2023 Jun 30;80(2):119-125. doi: 10.31053/1853.0605.v80.n2.40962.

2. Aydoğdu B, Azizoğlu M, Arslan S, Aydoğdu G, Basuguy E, Salık F, Ökten M, Hanifi-Okur M. Nuevo sistema de calificación diagnóstica para apendicitis pediátrica basado en parámetros hematológicos ajustados por edad y sexo. Gac Med Mex. 2023;159(2):106-12. English. doi: 10.24875/GMM.M22000750.

3. Reismann J, Romualdi A, Kiss N, Minderjahn MI, Kallarackal J, Schad M, Reismann M. Diagnosis and classification of pediatric acute appendicitis by artificial intelligence methods: An investigator-independent approach. PLoS One. 2019 Sep 25;14(9):e0222030. doi: 10.1371/journal.pone.0222030.

4. Aydin E, Türkmen İU, Namli G, Öztürk Ç, Esen AB, Eray YN, Eroğlu E, Akova F. A novel and simple machine learning algorithm for preoperative diagnosis of acute appendicitis in children. Pediatr Surg Int. 2020 Jun;36(6):735-742. doi: 10.1007/s00383-020-04655-7.

5. Marcinkevics R, Reis Wolfertstetter P, Wellmann S, Knorr C, Vogt JE. Using Machine Learning to Predict the Diagnosis, Management and Severity of Pediatric Appendicitis. Front Pediatr. 2021 Apr 29;9:662183. doi: 10.3389/fped.2021.662183.

Published

2024-03-27

Issue

Section

Cartas al Director

How to Cite

1.
Arango Cárdenas D, Castrillón Lozano JA, Areiza Ocampo X. Predictive appendicitis scale for children under 4 years of age : Is it possible to apply artificial intelligence?. Rev Fac Cien Med Univ Nac Cordoba [Internet]. 2024 Mar. 27 [cited 2024 Nov. 21];81(1):196-203. Available from: https://revistas.psi.unc.edu.ar/index.php/med/article/view/44316

Similar Articles

1-10 of 116

You may also start an advanced similarity search for this article.