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.
| Originalsprog | Engelsk |
|---|---|
| Titel | Proceedings of the Joint 25th Nordic Conference on Computational Linguistics and 11th Baltic Conference on Human Language Technologies (NoDaLiDa/Baltic-HLT) |
| Antal sider | 15 |
| Forlag | University of Tartu Library |
| Publikationsdato | mar. 2025 |
| Sider | 739-754 |
| Artikelnummer | 57 |
| Status | Udgivet - mar. 2025 |
| Begivenhed | 25th Nordic Conference on Computational Linguistics and 11th Baltic Conference on Human Language Technologies - Tallinn, Estland Varighed: 2 mar. 2025 → 5 mar. 2025 Konferencens nummer: 25 https://www.nodalida-bhlt2025.eu/conference |
Konference
| Konference | 25th Nordic Conference on Computational Linguistics and 11th Baltic Conference on Human Language Technologies |
|---|---|
| Nummer | 25 |
| Land/Område | Estland |
| By | Tallinn |
| Periode | 02/03/2025 → 05/03/2025 |
| Internetadresse |