Abstract
Reliable automatic solutions to extract structured information from free-text nursing notes could bring important efficiency gains in healthcare, but their development is hampered by the sensitivity and limited availability of example data. We describe a method for eliciting fictitious nursing documentation and associated structured documentation from volunteers and a resulting dataset of 397 Danish notes collected and annotated through a custom web application from 98 participating nurses. After some manual refinement, we obtained a high-quality dataset containing nurse notes with relevant entities identified. We describe the implementation and limitations of our approach as well as initial experiments in a named entity tagging setup.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the Joint 25th Nordic Conference on Computational Linguistics and 11th Baltic Conference on Human Language Technologies (NoDaLiDa/Baltic-HLT) |
| Number of pages | 15 |
| Publisher | University of Tartu Library |
| Publication date | Mar 2025 |
| Pages | 739-754 |
| Article number | 57 |
| Publication status | Published - Mar 2025 |
| Event | Computational Linguistics and Human Language Technologies - Estonia, Tallinn, Estonia Duration: 2 Mar 2025 → 5 Mar 2025 Conference number: 25 https://www.nodalida-bhlt2025.eu/conference |
Conference
| Conference | Computational Linguistics and Human Language Technologies |
|---|---|
| Number | 25 |
| Location | Estonia |
| Country/Territory | Estonia |
| City | Tallinn |
| Period | 02/03/2025 → 05/03/2025 |
| Internet address |
Keywords
- Nursing documentation
- Automatic information extraction
- Sensitive data challenges
- Fictitious data generation
- Named entity tagging
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