GraSCCo_PII_V2 - Graz Synthetic Clinical text Corpus with PII Annotations

GraSCCo_PII_V2 - Graz Synthetic Clinical text Corpus with Personally Identifiable Informations

Additional source of:

Lohr C, Faller J, Riedel A, Nguyen HM, Wolfien M, Hofenbitzer J, Modersohn L, Romberg J, Prasser F, Omeirat J, Wen Y, Galusch O, Hahn U, Seiferling M, Dieterich C, Klügl P, Matthies F, Kind J, Boeker M, Löffler M, Meineke F. GeMTeX's De-Identification in Action: Lessons Learned & Devil's Details. Stud Health Technol Inform. 2025 Sep 3;331:274-282. doi: 10.3233/SHTI251406. PMID: 40899551. (https://pubmed.ncbi.nlm.nih.gov/40899551/)

GraSCCo  is a collection of artificially generated semi-structured and unstructured German-language clinical summaries. These summaries are formulated as letters from the hospital to the patient's GP after in-patient or out-patient care. Details:

Stefan Schulz. (2022). GraSCCo (Version v1) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.6539131

Modersohn L, Schulz S, Lohr C, Hahn U. GRASCCO - The First Publicly Shareable, Multiply-Alienated German Clinical Text Corpus. Stud Health Technol Inform. 2022;296:66-72. doi:10.3233/SHTI220805

First Version - GraSSCo with PHI (now named as PII) annotations as external source of

Lohr C, Matthies F, Faller J, et al. De-Identifying GRASCCO - A Pilot Study for the De-Identification of the German Medical Text Project (GeMTeX) Corpus. Stud Health Technol Inform. 2024;317:171-179. doi:10.3233/SHTI240853 (https://pubmed.ncbi.nlm.nih.gov/39234720/)

This repository contains the annotations in XMI and JSON exports created with the INCEpTION annotation platform (https://inception-project.github.io/), also the annotation guideline document, TypeSystem.xml and layer.json (needed for import in INCEpTION), see also https://github.com/dkpro/dkpro-cassis.