@inproceedings{pilan-etal-2020-classification,
title = "Classification of Syncope Cases in {N}orwegian Medical Records",
author = "Pilan, Ildiko and
Brekke, P{\aa}l H. and
Dahl, Fredrik A. and
Gundersen, Tore and
Husby, Haldor and
Nytr{\o}, {\O}ystein and
{\O}vrelid, Lilja",
booktitle = "Proceedings of the 3rd Clinical Natural Language Processing Workshop",
month = nov,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.clinicalnlp-1.9",
doi = "10.18653/v1/2020.clinicalnlp-1.9",
pages = "79--84",
abstract = "Loss of consciousness, so-called syncope, is a commonly occurring symptom associated with worse prognosis for a number of heart-related diseases. We present a comparison of methods for a diagnosis classification task in Norwegian clinical notes, targeting syncope, i.e. fainting cases. We find that an often neglected baseline with keyword matching constitutes a rather strong basis, but more advanced methods do offer some improvement in classification performance, especially a convolutional neural network model. The developed pipeline is planned to be used for quantifying unregistered syncope cases in Norway.",
}
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<abstract>Loss of consciousness, so-called syncope, is a commonly occurring symptom associated with worse prognosis for a number of heart-related diseases. We present a comparison of methods for a diagnosis classification task in Norwegian clinical notes, targeting syncope, i.e. fainting cases. We find that an often neglected baseline with keyword matching constitutes a rather strong basis, but more advanced methods do offer some improvement in classification performance, especially a convolutional neural network model. The developed pipeline is planned to be used for quantifying unregistered syncope cases in Norway.</abstract>
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%0 Conference Proceedings
%T Classification of Syncope Cases in Norwegian Medical Records
%A Pilan, Ildiko
%A Brekke, Pål H.
%A Dahl, Fredrik A.
%A Gundersen, Tore
%A Husby, Haldor
%A Nytrø, Øystein
%A Øvrelid, Lilja
%S Proceedings of the 3rd Clinical Natural Language Processing Workshop
%D 2020
%8 nov
%I Association for Computational Linguistics
%C Online
%F pilan-etal-2020-classification
%X Loss of consciousness, so-called syncope, is a commonly occurring symptom associated with worse prognosis for a number of heart-related diseases. We present a comparison of methods for a diagnosis classification task in Norwegian clinical notes, targeting syncope, i.e. fainting cases. We find that an often neglected baseline with keyword matching constitutes a rather strong basis, but more advanced methods do offer some improvement in classification performance, especially a convolutional neural network model. The developed pipeline is planned to be used for quantifying unregistered syncope cases in Norway.
%R 10.18653/v1/2020.clinicalnlp-1.9
%U https://aclanthology.org/2020.clinicalnlp-1.9
%U https://doi.org/10.18653/v1/2020.clinicalnlp-1.9
%P 79-84
Markdown (Informal)
[Classification of Syncope Cases in Norwegian Medical Records](https://aclanthology.org/2020.clinicalnlp-1.9) (Pilan et al., ClinicalNLP 2020)
ACL
- Ildiko Pilan, Pål H. Brekke, Fredrik A. Dahl, Tore Gundersen, Haldor Husby, Øystein Nytrø, and Lilja Øvrelid. 2020. Classification of Syncope Cases in Norwegian Medical Records. In Proceedings of the 3rd Clinical Natural Language Processing Workshop, pages 79–84, Online. Association for Computational Linguistics.