Annotating Health Records: Does Ground Truth Even Exist?
| Authors | |
|---|---|
| Year of publication | 2024 |
| Type | Article in Proceedings |
| Conference | Proceedings of the Eighteenth Workshop on Recent Advances in Slavonic Natural Languages Processing, RASLAN 2024 |
| MU Faculty or unit | |
| Citation | |
| web | https://nlp.fi.muni.cz/raslan/2024/paper12.pdf |
| Keywords | Czech; Electronic health records; EHR; annotation; named entity recognition; NER; medical concept mining |
| Description | This paper introduces a new ground truth subset of the CSEHR dataset, a dataset of Czech health records annotated using a schema of 14 classes that is an adapted version of Apache cTAKES Core Clinical Element types. The paper details the considerations involved in (re)defining individual annotation classes in attempts to maximize utility in computational understanding of medical text. |
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