Using Electronic Patient Records to Discover Disease Correlations and Stratify Patient Cohorts

Francisco S. Roque, Peter B. Jensen, Henriette Schmock, Marlene Dalgaard, Massimo Andreatta, Thomas Hansen, Karen Søeby, Søren Bredkjaer, Anders Juul, Thomas Werge, Lars J. Jensen, Søren Brunak

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    Abstract

    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.
    Original languageEnglish
    JournalP L o S Computational Biology (Online)
    Volume7
    Issue number8
    ISSN1553-7358
    DOIs
    Publication statusPublished - 2011

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