@inproceedings{alekseev-etal-2022-medical,
title = "Medical Crossing: a Cross-lingual Evaluation of Clinical Entity Linking",
author = "Alekseev, Anton and
Miftahutdinov, Zulfat and
Tutubalina, Elena and
Shelmanov, Artem and
Ivanov, Vladimir and
Kokh, Vladimir and
Nesterov, Alexander and
Avetisian, Manvel and
Chertok, Andrei and
Nikolenko, Sergey",
editor = "Calzolari, Nicoletta and
B{\'e}chet, Fr{\'e}d{\'e}ric and
Blache, Philippe and
Choukri, Khalid and
Cieri, Christopher and
Declerck, Thierry and
Goggi, Sara and
Isahara, Hitoshi and
Maegaard, Bente and
Mariani, Joseph and
Mazo, H{\'e}l{\`e}ne and
Odijk, Jan and
Piperidis, Stelios",
booktitle = "Proceedings of the Thirteenth Language Resources and Evaluation Conference",
month = jun,
year = "2022",
address = "Marseille, France",
publisher = "European Language Resources Association",
url = "https://aclanthology.org/2022.lrec-1.447",
pages = "4212--4220",
abstract = "Medical data annotation requires highly qualified expertise. Despite the efforts devoted to medical entity linking in different languages, available data is very sparse in terms of both data volume and languages. In this work, we establish benchmarks for cross-lingual medical entity linking using clinical reports, clinical guidelines, and medical research papers. We present a test set filtering procedure designed to analyze the {``}hard cases{''} of entity linking approaching zero-shot cross-lingual transfer learning, evaluate state-of-the-art models, and draw several interesting conclusions based on our evaluation results.",
}
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<abstract>Medical data annotation requires highly qualified expertise. Despite the efforts devoted to medical entity linking in different languages, available data is very sparse in terms of both data volume and languages. In this work, we establish benchmarks for cross-lingual medical entity linking using clinical reports, clinical guidelines, and medical research papers. We present a test set filtering procedure designed to analyze the “hard cases” of entity linking approaching zero-shot cross-lingual transfer learning, evaluate state-of-the-art models, and draw several interesting conclusions based on our evaluation results.</abstract>
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%0 Conference Proceedings
%T Medical Crossing: a Cross-lingual Evaluation of Clinical Entity Linking
%A Alekseev, Anton
%A Miftahutdinov, Zulfat
%A Tutubalina, Elena
%A Shelmanov, Artem
%A Ivanov, Vladimir
%A Kokh, Vladimir
%A Nesterov, Alexander
%A Avetisian, Manvel
%A Chertok, Andrei
%A Nikolenko, Sergey
%Y Calzolari, Nicoletta
%Y Béchet, Frédéric
%Y Blache, Philippe
%Y Choukri, Khalid
%Y Cieri, Christopher
%Y Declerck, Thierry
%Y Goggi, Sara
%Y Isahara, Hitoshi
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Mazo, Hélène
%Y Odijk, Jan
%Y Piperidis, Stelios
%S Proceedings of the Thirteenth Language Resources and Evaluation Conference
%D 2022
%8 June
%I European Language Resources Association
%C Marseille, France
%F alekseev-etal-2022-medical
%X Medical data annotation requires highly qualified expertise. Despite the efforts devoted to medical entity linking in different languages, available data is very sparse in terms of both data volume and languages. In this work, we establish benchmarks for cross-lingual medical entity linking using clinical reports, clinical guidelines, and medical research papers. We present a test set filtering procedure designed to analyze the “hard cases” of entity linking approaching zero-shot cross-lingual transfer learning, evaluate state-of-the-art models, and draw several interesting conclusions based on our evaluation results.
%U https://aclanthology.org/2022.lrec-1.447
%P 4212-4220
Markdown (Informal)
[Medical Crossing: a Cross-lingual Evaluation of Clinical Entity Linking](https://aclanthology.org/2022.lrec-1.447) (Alekseev et al., LREC 2022)
ACL
- Anton Alekseev, Zulfat Miftahutdinov, Elena Tutubalina, Artem Shelmanov, Vladimir Ivanov, Vladimir Kokh, Alexander Nesterov, Manvel Avetisian, Andrei Chertok, and Sergey Nikolenko. 2022. Medical Crossing: a Cross-lingual Evaluation of Clinical Entity Linking. In Proceedings of the Thirteenth Language Resources and Evaluation Conference, pages 4212–4220, Marseille, France. European Language Resources Association.