Selection of genetic and phenotypic features associated with inflammatory status of patients on dialysis using relaxed linear separability method.

Identification of risk factors in patients with a particular disease can be analyzed in clinical data sets by using feature selection procedures of pattern recognition and data mining methods. The applicability of the relaxed linear separability (RLS) method of feature subset selection was checked f...

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Autores principales:	Leon Bobrowski, Tomasz Łukaszuk, Bengt Lindholm, Peter Stenvinkel, Olof Heimburger, Jonas Axelsson, Peter Bárány, Juan Jesus Carrero, Abdul Rashid Qureshi, Karin Luttropp, Malgorzata Debowska, Louise Nordfors, Martin Schalling, Jacek Waniewski
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2014
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/0ed82540aed94ce3a435002ee2463c0e
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spelling	oai:doaj.org-article:0ed82540aed94ce3a435002ee2463c0e2021-11-18T08:35:23ZSelection of genetic and phenotypic features associated with inflammatory status of patients on dialysis using relaxed linear separability method.1932-620310.1371/journal.pone.0086630https://doaj.org/article/0ed82540aed94ce3a435002ee2463c0e2014-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24489753/?tool=EBIhttps://doaj.org/toc/1932-6203Identification of risk factors in patients with a particular disease can be analyzed in clinical data sets by using feature selection procedures of pattern recognition and data mining methods. The applicability of the relaxed linear separability (RLS) method of feature subset selection was checked for high-dimensional and mixed type (genetic and phenotypic) clinical data of patients with end-stage renal disease. The RLS method allowed for substantial reduction of the dimensionality through omitting redundant features while maintaining the linear separability of data sets of patients with high and low levels of an inflammatory biomarker. The synergy between genetic and phenotypic features in differentiation between these two subgroups was demonstrated.Leon BobrowskiTomasz ŁukaszukBengt LindholmPeter StenvinkelOlof HeimburgerJonas AxelssonPeter BárányJuan Jesus CarreroAbdul Rashid QureshiKarin LuttroppMalgorzata DebowskaLouise NordforsMartin SchallingJacek WaniewskiPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 9, Iss 1, p e86630 (2014)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Leon Bobrowski Tomasz Łukaszuk Bengt Lindholm Peter Stenvinkel Olof Heimburger Jonas Axelsson Peter Bárány Juan Jesus Carrero Abdul Rashid Qureshi Karin Luttropp Malgorzata Debowska Louise Nordfors Martin Schalling Jacek Waniewski Selection of genetic and phenotypic features associated with inflammatory status of patients on dialysis using relaxed linear separability method.
description	Identification of risk factors in patients with a particular disease can be analyzed in clinical data sets by using feature selection procedures of pattern recognition and data mining methods. The applicability of the relaxed linear separability (RLS) method of feature subset selection was checked for high-dimensional and mixed type (genetic and phenotypic) clinical data of patients with end-stage renal disease. The RLS method allowed for substantial reduction of the dimensionality through omitting redundant features while maintaining the linear separability of data sets of patients with high and low levels of an inflammatory biomarker. The synergy between genetic and phenotypic features in differentiation between these two subgroups was demonstrated.
format	article
author	Leon Bobrowski Tomasz Łukaszuk Bengt Lindholm Peter Stenvinkel Olof Heimburger Jonas Axelsson Peter Bárány Juan Jesus Carrero Abdul Rashid Qureshi Karin Luttropp Malgorzata Debowska Louise Nordfors Martin Schalling Jacek Waniewski
author_facet	Leon Bobrowski Tomasz Łukaszuk Bengt Lindholm Peter Stenvinkel Olof Heimburger Jonas Axelsson Peter Bárány Juan Jesus Carrero Abdul Rashid Qureshi Karin Luttropp Malgorzata Debowska Louise Nordfors Martin Schalling Jacek Waniewski
author_sort	Leon Bobrowski
title	Selection of genetic and phenotypic features associated with inflammatory status of patients on dialysis using relaxed linear separability method.
title_short	Selection of genetic and phenotypic features associated with inflammatory status of patients on dialysis using relaxed linear separability method.
title_full	Selection of genetic and phenotypic features associated with inflammatory status of patients on dialysis using relaxed linear separability method.
title_fullStr	Selection of genetic and phenotypic features associated with inflammatory status of patients on dialysis using relaxed linear separability method.
title_full_unstemmed	Selection of genetic and phenotypic features associated with inflammatory status of patients on dialysis using relaxed linear separability method.
title_sort	selection of genetic and phenotypic features associated with inflammatory status of patients on dialysis using relaxed linear separability method.
publisher	Public Library of Science (PLoS)
publishDate	2014
url	https://doaj.org/article/0ed82540aed94ce3a435002ee2463c0e
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Selection of genetic and phenotypic features associated with inflammatory status of patients on dialysis using relaxed linear separability method.

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