Journal article
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 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.
Language: | English |
---|---|
Publisher: | Public Library of Science |
Year: | 2011 |
Pages: | e1002141 |
ISSN: | 15537358 and 1553734x |
Types: | Journal article |
DOI: | 10.1371/journal.pcbi.1002141 |
ORCIDs: | 0000-0002-0534-4350 , 0000-0001-7885-715X and 0000-0003-0316-5866 |