Integrating phenotypic data from electronic patient records with molecular level systems biology: Abstract of invited lecture

Publication: Research - peer-reviewConference article – Annual report year: 2011

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Integrating phenotypic data from electronic patient records with molecular level systems biology : Abstract of invited lecture. / Brunak, Søren (Invited author).

In: FEBS JOURNAL, Vol. 278, No. Suppl. s1, 2011, p. 27.

Publication: Research - peer-reviewConference article – Annual report year: 2011

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Brunak, Søren (Invited author) / Integrating phenotypic data from electronic patient records with molecular level systems biology : Abstract of invited lecture.

In: FEBS JOURNAL, Vol. 278, No. Suppl. s1, 2011, p. 27.

Publication: Research - peer-reviewConference article – Annual report year: 2011

Bibtex

@article{4709a4e131d7467396f40d917fe038ec,
title = "Integrating phenotypic data from electronic patient records with molecular level systems biology: Abstract of invited lecture",
publisher = "Wiley-Blackwell Publishing Ltd.",
author = "Søren Brunak",
year = "2011",
doi = "10.1111/j.1742-4658.2011.08136.x",
volume = "278",
number = "Suppl. s1",
pages = "27",
journal = "FEBS JOURNAL",
issn = "1742-464X",

}

RIS

TY - CONF

T1 - Integrating phenotypic data from electronic patient records with molecular level systems biology

T2 - Abstract of invited lecture

A1 - Brunak,Søren

AU - Brunak,Søren

PB - Wiley-Blackwell Publishing Ltd.

PY - 2011

Y1 - 2011

N2 - 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 are mapped to systems biology frameworks.

AB - 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 are mapped to systems biology frameworks.

UR - http://www.febs2011.it/

U2 - 10.1111/j.1742-4658.2011.08136.x

DO - 10.1111/j.1742-4658.2011.08136.x

JO - FEBS JOURNAL

JF - FEBS JOURNAL

SN - 1742-464X

IS - Suppl. s1

VL - 278

SP - 27

ER -