De-identifying Swedish clinical text - refinement of a gold standard and experiments with Conditional random fields.

ABSTRACT:

Background

In order to perform research on the information contained in Electronic Patient Records (EPRs), access to the data itself is needed. This is often very difficult due to confidentiality regulations. The data sets need to be fully de-identified before they can be distributed to researchers. De-identification is a difficult task where the definitions of annotation classes are not self-evident.

Results

We present work on the creation of two refined variants of a manually annotated Gold standard for de-identification, one created automatically, and one created through discussions among the annotators. The data is a subset from the Stockholm EPR Corpus, a data set available within our research group. These are used for the training and evaluation of an automatic system

SUBMITTER: Dalianis H 

PROVIDER: S-EPMC2895734 | biostudies-literature | 2010 Apr

REPOSITORIES: biostudies-literature