  Cardiovascular disease (CVD) has become the leading cause of death in China,
and most of the cases can be prevented by controlling risk factors. The goal of
this study was to build a corpus of CVD risk factor annotations based on
Chinese electronic medical records (CEMRs). This corpus is intended to be used
to develop a risk factor information extraction system that, in turn, can be
applied as a foundation for the further study of the progress of risk factors
and CVD. We designed a light annotation task to capture CVD risk factors with
indicators, temporal attributes and assertions that were explicitly or
implicitly displayed in the records. The task included: 1) preparing data; 2)
creating guidelines for capturing annotations (these were created with the help
of clinicians); 3) proposing an annotation method including building the
guidelines draft, training the annotators and updating the guidelines, and
corpus construction. Then, a risk factor annotated corpus based on
de-identified discharge summaries and progress notes from 600 patients was
developed. Built with the help of clinicians, this corpus has an
inter-annotator agreement (IAA) F1-measure of 0.968, indicating a high
reliability. To the best of our knowledge, this is the first annotated corpus
concerning CVD risk factors in CEMRs and the guidelines for capturing CVD risk
factor annotations from CEMRs were proposed. The obtained document-level
annotations can be applied in future studies to monitor risk factors and CVD
over the long term.
