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.
|Issue number||Suppl. s1|
|Publication status||Published - 2011|
|Event||FEBS Congress : Biochemistry for Tomorrows Medicine - Torino, Italy|
Duration: 1 Jan 2011 → …
Conference number: 36
|Conference||FEBS Congress : Biochemistry for Tomorrows Medicine|
|Period||01/01/2011 → …|