Feature Selection for Dengue using Principal Component Analysis

Autores

  • Julia Figueredo
  • Christian E. Schaerer
  • Santiago Gómez Guerrero
  • Gustavo Sosa-Cabrera
  • Alejandra Rojas
  • Cynthia Bernal
  • Fátima Cardozo
  • Teresita Báez

Resumo

Dengue fever is one of the top ten global health threats, is endemic in more than 100 countries [1]. In Paraguay, dengue has been endemic since 2009. When an outbreak occurs, the number of non-recorded and under-registered cases increases due to the fact that confirmatory analyses are, specially for developing countries, complex and expensive. For that reason, these laboratory tests are not fully available. In these situations, detection of dengue cases becomes an important issue. The problem consists of establishing some variables (associated with traditional laboratory results) to determine a positive and a severe case of dengue [2]. [...]

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Biografia do Autor

Julia Figueredo

Polytechnic School, National University of Asuncion, San Lorenzo, Paraguay

Christian E. Schaerer

Polytechnic School, National University of Asuncion, San Lorenzo, Paraguay

Santiago Gómez Guerrero

Polytechnic School, National University of Asuncion, San Lorenzo, Paraguay

Gustavo Sosa-Cabrera

Polytechnic School, National University of Asuncion, San Lorenzo, Paraguay

Alejandra Rojas

Institute for Health Science, National University of Asuncion, San Lorenzo, Paraguay

Cynthia Bernal

Institute for Health Science, National University of Asuncion, San Lorenzo, Paraguay

Fátima Cardozo

Institute for Health Science, National University of Asuncion, San Lorenzo, Paraguay

Teresita Báez

ASESTPY, Paraguayan Association of Statisticians, Asunción, Paraguay

Referências

OPS(Organización Panamericana de la Salud)/OMS(Organización Mundial de la Salud. Módulo de Principios de Epidemiologia para el control de enfermedades. 2a ed. N.W. Washington, D.C., 2001. https://www.paho.org/col/dmdocuments/MOPECE5.pdf.

A. Rojas, F. Cardozo, C. Cantero, V. Stittleburg, S. López, C.M. Bernal, F. Giménez, L.P. Mendoza, B. Pinsky, Y. Guillén, M. Páez, and J. Jesse. “Characterization of dengue cases among patients with an acute illness, Central Department, Paraguay.” In: PeerJ (2019). url: https://doi.org/10.7717/peerj.7852.

S. Gómez-Guerrero, M. García-Torres, G. Sosa-Cabrera, E.G. Sotto-Riveros, and C.E. Schaerer. “Classifying dengue cases using CatPCA in combination with the MSU correlation”. In: Proceedings of the Entropy 2021: The Scientific Tool of the 21st Century, 5–7 May, MDPI. 2021. doi: 10.3390/Entropy2021-09828.

S. Gómez-Guerrero, I. Ortiz, G. Sosa-Cabrera, M. García-Torres, and C.E. Schaerer. “Measuring Interactions in Categorical Datasets Using Multivariate Symmetrical Uncertainty”. In: Entropy (2022). url: https://doi.org/10.3390/e24010064.

R. Arias-Michel, M. García-Torres, C.E. Schaerer, and F. Divina. “Feature Selection Using Approximate Multivariate Markov Blankets”. In: Hybrid Artificial Intelligent Systems. Ed. by Francisco Martínez-Álvarez, Alicia Troncoso, Héctor Quintián, and Emilio Corchado. Cham: Springer International Publishing, 2016, pp. 114–125. isbn: 978-3-319-32034-2.

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Publicado

2023-12-18

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