@inproceedings{roller-etal-2016-fine,
title = "A fine-grained corpus annotation schema of {G}erman nephrology records",
author = "Roller, Roland and
Uszkoreit, Hans and
Xu, Feiyu and
Seiffe, Laura and
Mikhailov, Michael and
Staeck, Oliver and
Budde, Klemens and
Halleck, Fabian and
Schmidt, Danilo",
editor = "Rumshisky, Anna and
Roberts, Kirk and
Bethard, Steven and
Naumann, Tristan",
booktitle = "Proceedings of the Clinical Natural Language Processing Workshop ({C}linical{NLP})",
month = dec,
year = "2016",
address = "Osaka, Japan",
publisher = "The COLING 2016 Organizing Committee",
url = "https://aclanthology.org/W16-4210",
pages = "69--77",
abstract = "In this work we present a fine-grained annotation schema to detect named entities in German clinical data of chronically ill patients with kidney diseases. The annotation schema is driven by the needs of our clinical partners and the linguistic aspects of German language. In order to generate annotations within a short period, the work also presents a semi-automatic annotation which uses additional sources of knowledge such as UMLS, to pre-annotate concepts in advance. The presented schema will be used to apply novel techniques from natural language processing and machine learning to support doctors treating their patients by improved information access from unstructured German texts.",
}
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<abstract>In this work we present a fine-grained annotation schema to detect named entities in German clinical data of chronically ill patients with kidney diseases. The annotation schema is driven by the needs of our clinical partners and the linguistic aspects of German language. In order to generate annotations within a short period, the work also presents a semi-automatic annotation which uses additional sources of knowledge such as UMLS, to pre-annotate concepts in advance. The presented schema will be used to apply novel techniques from natural language processing and machine learning to support doctors treating their patients by improved information access from unstructured German texts.</abstract>
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%0 Conference Proceedings
%T A fine-grained corpus annotation schema of German nephrology records
%A Roller, Roland
%A Uszkoreit, Hans
%A Xu, Feiyu
%A Seiffe, Laura
%A Mikhailov, Michael
%A Staeck, Oliver
%A Budde, Klemens
%A Halleck, Fabian
%A Schmidt, Danilo
%Y Rumshisky, Anna
%Y Roberts, Kirk
%Y Bethard, Steven
%Y Naumann, Tristan
%S Proceedings of the Clinical Natural Language Processing Workshop (ClinicalNLP)
%D 2016
%8 December
%I The COLING 2016 Organizing Committee
%C Osaka, Japan
%F roller-etal-2016-fine
%X In this work we present a fine-grained annotation schema to detect named entities in German clinical data of chronically ill patients with kidney diseases. The annotation schema is driven by the needs of our clinical partners and the linguistic aspects of German language. In order to generate annotations within a short period, the work also presents a semi-automatic annotation which uses additional sources of knowledge such as UMLS, to pre-annotate concepts in advance. The presented schema will be used to apply novel techniques from natural language processing and machine learning to support doctors treating their patients by improved information access from unstructured German texts.
%U https://aclanthology.org/W16-4210
%P 69-77
Markdown (Informal)
[A fine-grained corpus annotation schema of German nephrology records](https://aclanthology.org/W16-4210) (Roller et al., ClinicalNLP 2016)
ACL
- Roland Roller, Hans Uszkoreit, Feiyu Xu, Laura Seiffe, Michael Mikhailov, Oliver Staeck, Klemens Budde, Fabian Halleck, and Danilo Schmidt. 2016. A fine-grained corpus annotation schema of German nephrology records. In Proceedings of the Clinical Natural Language Processing Workshop (ClinicalNLP), pages 69–77, Osaka, Japan. The COLING 2016 Organizing Committee.