Patient-friendly Clinical Notes: Towards a new Text Simplification Dataset
Jan Trienes, Jörg Schlötterer, Hans-Ulrich Schildhaus, Christin Seifert
Abstract
Automatic text simplification can help patients to better understand their own clinical notes. A major hurdle for the development of clinical text simplification methods is the lack of high quality resources. We report ongoing efforts in creating a parallel dataset of professionally simplified clinical notes. Currently, this corpus consists of 851 document-level simplifications of German pathology reports. We highlight characteristics of this dataset and establish first baselines for paragraph-level simplification.- Anthology ID:
- 2022.tsar-1.3
- Volume:
- Proceedings of the Workshop on Text Simplification, Accessibility, and Readability (TSAR-2022)
- Month:
- December
- Year:
- 2022
- Address:
- Abu Dhabi, United Arab Emirates (Virtual)
- Editors:
- Sanja Štajner, Horacio Saggion, Daniel Ferrés, Matthew Shardlow, Kim Cheng Sheang, Kai North, Marcos Zampieri, Wei Xu
- Venue:
- TSAR
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 19–27
- Language:
- URL:
- https://aclanthology.org/2022.tsar-1.3
- DOI:
- 10.18653/v1/2022.tsar-1.3
- Cite (ACL):
- Jan Trienes, Jörg Schlötterer, Hans-Ulrich Schildhaus, and Christin Seifert. 2022. Patient-friendly Clinical Notes: Towards a new Text Simplification Dataset. In Proceedings of the Workshop on Text Simplification, Accessibility, and Readability (TSAR-2022), pages 19–27, Abu Dhabi, United Arab Emirates (Virtual). Association for Computational Linguistics.
- Cite (Informal):
- Patient-friendly Clinical Notes: Towards a new Text Simplification Dataset (Trienes et al., TSAR 2022)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/2022.tsar-1.3.pdf