| Literature DB >> 30815119 |
Christina Lohr1, Stephanie Luther1, Franz Matthies1, Luise Modersohn1, Danny Ammon2, Kutaiba Saleh2, Andreas G Henkel2, Michael Kiehntopf3, Udo Hahn1.
Abstract
We present the outcome of an annotation effort targeting the content-sensitive segmentation of German clinical reports into sections. We recruited an annotation team of up to eight medical students to annotate a clinical text corpus on a sentence-by-sentence basis in four pre-annotation iterations and one final main annotation step. The annotation scheme we came up with adheres to categories developed for clinical documents in the HL7-CDA (Clinical Document Architecture) standard for section headings. Once the scheme became stable, we ran the main annotation campaign on the complete set of roughly 1,000 clinical documents. Due to its reliance on the CDA standard, the annotation scheme allows the integration of legacy and newly produced clinical documents within a common pipeline. We then made direct use of the annotations by training a baseline classifier to automatically identify sections in clinical reports.Entities:
Mesh:
Year: 2018 PMID: 30815119 PMCID: PMC6371337
Source DB: PubMed Journal: AMIA Annu Symp Proc ISSN: 1559-4076