Vitenskapelig Kapittel/Artikkel/Konferanseartikkel   2020

Pilán, Ildikó; Brekke, Pål Haugar; Dahl, Fredrik Andreas; Gundersen, Tore; Husby, Haldor; Nytrø, Øystein; Øvrelid, Lilja

Publikasjonsdetaljer

Sider:

79–84

År:

2020

Lenker:

FULLTEKST: www.aclweb.org/anthology/2020.clinicalnlp-1.9.pdf
DOI: doi.org/10.18653/v1/2020.clinicalnlp-1.9

Del av: Proceedings of the 3rd Clinical Natural Language Processing Workshop (Association for Computational Linguistics, 2020)

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.