An Evolutionary Approach to the Annotation of Discharge Summaries.
Annotation guideline
Clinical text corpus
German discharge summaries
Journal
Studies in health technology and informatics
ISSN: 1879-8365
Titre abrégé: Stud Health Technol Inform
Pays: Netherlands
ID NLM: 9214582
Informations de publication
Date de publication:
16 Jun 2020
16 Jun 2020
Historique:
entrez:
24
6
2020
pubmed:
24
6
2020
medline:
15
8
2020
Statut:
ppublish
Résumé
We here describe the evolution of annotation guidelines for major clinical named entities, namely Diagnosis, Findings and Symptoms, on a corpus of approximately 1,000 German discharge letters. Due to their intrinsic opaqueness and complexity, clinical annotation tasks require continuous guideline tuning, beginning from the initial definition of crucial entities and the subsequent iterative evolution of guidelines based on empirical evidence. We describe rationales for adaptation, with focus on several metrical criteria and task-centered clinical constraints.
Identifiants
pubmed: 32570340
pii: SHTI200116
doi: 10.3233/SHTI200116
doi:
Types de publication
Journal Article
Langues
eng