Partial least squares regression: A valuable method for modeling molecular behavior in hemodialysis

The aim of this work was to use the Partial Least Squares Regression (PLS) technique to fit simple models for the interpretation of an underlying complex process. In this study, the technique was used to build a statistical model for molecular kinetic data obtained from hemodialyzed patients. By usi...

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Detalles Bibliográficos
Autores principales: Fernández, Elmer Andrés, Valtuille, Rodolfo, Willshaw, Peter, Balzarini, M.
Formato: Artículo
Lenguaje:Español
Publicado: 2008
Materias:
TA Ingeniería de asistencia técnica (General). Ingeniería Civil (General)
Acceso en línea:http://pa.bibdigital.ucc.edu.ar/4808/1/A_Fern%C3%A1ndez.pdf
Aporte de:
Producción Académica Universidad Católica de Córdoba (UCCor) de Universidad Católica de Córdoba
id I38-R144-4808
record_format dspace
spelling I38-R144-48082025-04-28T18:02:23Z http://pa.bibdigital.ucc.edu.ar/4808/ Partial least squares regression: A valuable method for modeling molecular behavior in hemodialysis Fernández, Elmer Andrés Valtuille, Rodolfo Willshaw, Peter Balzarini, M. TA Ingeniería de asistencia técnica (General). Ingeniería Civil (General) The aim of this work was to use the Partial Least Squares Regression (PLS) technique to fit simple models for the interpretation of an underlying complex process. In this study, the technique was used to build a statistical model for molecular kinetic data obtained from hemodialyzed patients. By using PLS we derived statistical linear models for the prediction of the equilibrated urea concentration which would be reached 30-60 min after the end of the dialysis session. Models with an average relative prediction error (RPE) of less than 0.05% were achieved. The model predictive accuracy was evaluated in a cross-center study yielding an RPE < 3%. The chosen model was robust to variations such as sampling extraction time demonstrating a high capacity for modeling kinetics. It also was found to be useful for bedside monitoring. Finally, the PLS technique allowed identification of the most important co-variables in the model and of those patients with outlier patterns in their molecular dynamics. 2008-12-31 info:eu-repo/semantics/article info:eu-repo/semantics/closedAccess application/pdf spa http://pa.bibdigital.ucc.edu.ar/4808/1/A_Fern%C3%A1ndez.pdf Fernández, Elmer Andrés ORCID: https://orcid.org/0000-0002-4711-8634 <https://orcid.org/0000-0002-4711-8634>, Valtuille, Rodolfo ORCID: https://orcid.org/0000-0003-2434-9226 <https://orcid.org/0000-0003-2434-9226>, Willshaw, Peter and Balzarini, M. (2008) Partial least squares regression: A valuable method for modeling molecular behavior in hemodialysis. Annals of Biomedical Engineering, 36 (7). pp. 1305-1313. ISSN 15739686 info:eu-repo/semantics/altIdentifier/doi/10.1007/s10439-008-9492-1
institution Universidad Católica de Córdoba
institution_str I-38
repository_str R-144
collection Producción Académica Universidad Católica de Córdoba (UCCor)
language Español
orig_language_str_mv spa
topic TA Ingeniería de asistencia técnica (General). Ingeniería Civil (General)
spellingShingle TA Ingeniería de asistencia técnica (General). Ingeniería Civil (General)
Fernández, Elmer Andrés
Valtuille, Rodolfo
Willshaw, Peter
Balzarini, M.
Partial least squares regression: A valuable method for modeling molecular behavior in hemodialysis
topic_facet TA Ingeniería de asistencia técnica (General). Ingeniería Civil (General)
description The aim of this work was to use the Partial Least Squares Regression (PLS) technique to fit simple models for the interpretation of an underlying complex process. In this study, the technique was used to build a statistical model for molecular kinetic data obtained from hemodialyzed patients. By using PLS we derived statistical linear models for the prediction of the equilibrated urea concentration which would be reached 30-60 min after the end of the dialysis session. Models with an average relative prediction error (RPE) of less than 0.05% were achieved. The model predictive accuracy was evaluated in a cross-center study yielding an RPE < 3%. The chosen model was robust to variations such as sampling extraction time demonstrating a high capacity for modeling kinetics. It also was found to be useful for bedside monitoring. Finally, the PLS technique allowed identification of the most important co-variables in the model and of those patients with outlier patterns in their molecular dynamics.
format Artículo
author Fernández, Elmer Andrés
Valtuille, Rodolfo
Willshaw, Peter
Balzarini, M.
author_facet Fernández, Elmer Andrés
Valtuille, Rodolfo
Willshaw, Peter
Balzarini, M.
author_sort Fernández, Elmer Andrés
title Partial least squares regression: A valuable method for modeling molecular behavior in hemodialysis
title_short Partial least squares regression: A valuable method for modeling molecular behavior in hemodialysis
title_full Partial least squares regression: A valuable method for modeling molecular behavior in hemodialysis
title_fullStr Partial least squares regression: A valuable method for modeling molecular behavior in hemodialysis
title_full_unstemmed Partial least squares regression: A valuable method for modeling molecular behavior in hemodialysis
title_sort partial least squares regression: a valuable method for modeling molecular behavior in hemodialysis
publishDate 2008
url http://pa.bibdigital.ucc.edu.ar/4808/1/A_Fern%C3%A1ndez.pdf
work_keys_str_mv AT fernandezelmerandres partialleastsquaresregressionavaluablemethodformodelingmolecularbehaviorinhemodialysis
AT valtuillerodolfo partialleastsquaresregressionavaluablemethodformodelingmolecularbehaviorinhemodialysis
AT willshawpeter partialleastsquaresregressionavaluablemethodformodelingmolecularbehaviorinhemodialysis
AT balzarinim partialleastsquaresregressionavaluablemethodformodelingmolecularbehaviorinhemodialysis
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