I. Pilán, P. Brekke, F. A. Dahl, T. Gundersen, Haldor Husby, Ø. Nytrø, Lilja Øvrelid
{"title":"Classification of Syncope Cases in Norwegian Medical Records","authors":"I. Pilán, P. Brekke, F. A. Dahl, T. Gundersen, Haldor Husby, Ø. Nytrø, Lilja Øvrelid","doi":"10.18653/v1/2020.clinicalnlp-1.9","DOIUrl":null,"url":null,"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.","PeriodicalId":216954,"journal":{"name":"Clinical Natural Language Processing Workshop","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clinical Natural Language Processing Workshop","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18653/v1/2020.clinicalnlp-1.9","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
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.