@inproceedings{trienes-etal-2022-patient,
title = "Patient-friendly Clinical Notes: Towards a new Text Simplification Dataset",
author = {Trienes, Jan and
Schl{\"o}tterer, J{\"o}rg and
Schildhaus, Hans-Ulrich and
Seifert, Christin},
editor = "{\v{S}}tajner, Sanja and
Saggion, Horacio and
Ferr{\'e}s, Daniel and
Shardlow, Matthew and
Sheang, Kim Cheng and
North, Kai and
Zampieri, Marcos and
Xu, Wei",
booktitle = "Proceedings of the Workshop on Text Simplification, Accessibility, and Readability (TSAR-2022)",
month = dec,
year = "2022",
address = "Abu Dhabi, United Arab Emirates (Virtual)",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.tsar-1.3",
doi = "10.18653/v1/2022.tsar-1.3",
pages = "19--27",
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.",
}
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%0 Conference Proceedings
%T Patient-friendly Clinical Notes: Towards a new Text Simplification Dataset
%A Trienes, Jan
%A Schlötterer, Jörg
%A Schildhaus, Hans-Ulrich
%A Seifert, Christin
%Y Štajner, Sanja
%Y Saggion, Horacio
%Y Ferrés, Daniel
%Y Shardlow, Matthew
%Y Sheang, Kim Cheng
%Y North, Kai
%Y Zampieri, Marcos
%Y Xu, Wei
%S Proceedings of the Workshop on Text Simplification, Accessibility, and Readability (TSAR-2022)
%D 2022
%8 December
%I Association for Computational Linguistics
%C Abu Dhabi, United Arab Emirates (Virtual)
%F trienes-etal-2022-patient
%X 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.
%R 10.18653/v1/2022.tsar-1.3
%U https://aclanthology.org/2022.tsar-1.3
%U https://doi.org/10.18653/v1/2022.tsar-1.3
%P 19-27
Markdown (Informal)
[Patient-friendly Clinical Notes: Towards a new Text Simplification Dataset](https://aclanthology.org/2022.tsar-1.3) (Trienes et al., TSAR 2022)
ACL