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
are mapped to systems biology frameworks.
Original language | English |
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Journal | FEBS Journal |
Volume | 278 |
Issue number | Suppl. s1 |
Pages (from-to) | 27 |
ISSN | 1742-464X |
DOIs | |
Publication status | Published - 2011 |
Event | FEBS Congress : Biochemistry for Tomorrows Medicine - Torino, Italy Duration: 1 Jan 2011 → … Conference number: 36 |
Conference
Conference | FEBS Congress : Biochemistry for Tomorrows Medicine |
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Number | 36 |
City | Torino, Italy |
Period | 01/01/2011 → … |