Using electronic patient records to discover disease correlations and stratify patient cohorts.

Electronic patient records remain a rather unexplored, but potentially rich data source for discovering correlations between diseases. We describe a general approach for gathering phenotypic descriptions of patients from medical records in a systematic and non-cohort dependent manner. By extracting...

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Autores principales:	Francisco S Roque, Peter B Jensen, Henriette Schmock, Marlene Dalgaard, Massimo Andreatta, Thomas Hansen, Karen Søeby, Søren Bredkjær, Anders Juul, Thomas Werge, Lars J Jensen, Søren Brunak
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2011
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/99ba46806dcc46edb876c08be452b359
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spelling	oai:doaj.org-article:99ba46806dcc46edb876c08be452b3592021-11-18T05:50:20ZUsing electronic patient records to discover disease correlations and stratify patient cohorts.1553-734X1553-735810.1371/journal.pcbi.1002141https://doaj.org/article/99ba46806dcc46edb876c08be452b3592011-08-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/21901084/?tool=EBIhttps://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358Electronic patient records remain a rather unexplored, but potentially rich data source for discovering correlations between diseases. We describe a general approach for gathering phenotypic descriptions of patients from medical records in a systematic and non-cohort dependent manner. By extracting phenotype information from the free-text in such records we demonstrate that we can extend the information contained in the structured record data, and use it for producing fine-grained patient stratification and disease co-occurrence statistics. The approach uses a dictionary based on the International Classification of Disease ontology and is therefore in principle language independent. As a use case we show how records from a Danish psychiatric hospital lead to the identification of disease correlations, which subsequently can be mapped to systems biology frameworks.Francisco S RoquePeter B JensenHenriette SchmockMarlene DalgaardMassimo AndreattaThomas HansenKaren SøebySøren BredkjærAnders JuulThomas WergeLars J JensenSøren BrunakPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 7, Iss 8, p e1002141 (2011)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Francisco S Roque Peter B Jensen Henriette Schmock Marlene Dalgaard Massimo Andreatta Thomas Hansen Karen Søeby Søren Bredkjær Anders Juul Thomas Werge Lars J Jensen Søren Brunak Using electronic patient records to discover disease correlations and stratify patient cohorts.
description	Electronic patient records remain a rather unexplored, but potentially rich data source for discovering correlations between diseases. We describe a general approach for gathering phenotypic descriptions of patients from medical records in a systematic and non-cohort dependent manner. By extracting phenotype information from the free-text in such records we demonstrate that we can extend the information contained in the structured record data, and use it for producing fine-grained patient stratification and disease co-occurrence statistics. The approach uses a dictionary based on the International Classification of Disease ontology and is therefore in principle language independent. As a use case we show how records from a Danish psychiatric hospital lead to the identification of disease correlations, which subsequently can be mapped to systems biology frameworks.
format	article
author	Francisco S Roque Peter B Jensen Henriette Schmock Marlene Dalgaard Massimo Andreatta Thomas Hansen Karen Søeby Søren Bredkjær Anders Juul Thomas Werge Lars J Jensen Søren Brunak
author_facet	Francisco S Roque Peter B Jensen Henriette Schmock Marlene Dalgaard Massimo Andreatta Thomas Hansen Karen Søeby Søren Bredkjær Anders Juul Thomas Werge Lars J Jensen Søren Brunak
author_sort	Francisco S Roque
title	Using electronic patient records to discover disease correlations and stratify patient cohorts.
title_short	Using electronic patient records to discover disease correlations and stratify patient cohorts.
title_full	Using electronic patient records to discover disease correlations and stratify patient cohorts.
title_fullStr	Using electronic patient records to discover disease correlations and stratify patient cohorts.
title_full_unstemmed	Using electronic patient records to discover disease correlations and stratify patient cohorts.
title_sort	using electronic patient records to discover disease correlations and stratify patient cohorts.
publisher	Public Library of Science (PLoS)
publishDate	2011
url	https://doaj.org/article/99ba46806dcc46edb876c08be452b359
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Using electronic patient records to discover disease correlations and stratify patient cohorts.

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