Pilar López Úbeda, Manuel Carlos Díaz Galiano, L. Ureña López, Maite Martin
{"title":"Using Snomed to recognize and index chemical and drug mentions.","authors":"Pilar López Úbeda, Manuel Carlos Díaz Galiano, L. Ureña López, Maite Martin","doi":"10.18653/v1/D19-5718","DOIUrl":"https://doi.org/10.18653/v1/D19-5718","url":null,"abstract":"In this paper we describe a new named entity extraction system. Our work proposes a system for the identification and annotation of drug names in Spanish biomedical texts based on machine learning and deep learning models. Subsequently, a standardized code using Snomed is assigned to these drugs, for this purpose, Natural Language Processing tools and techniques have been used, and a dictionary of different sources of information has been built. The results are promising, we obtain 78% in F1 score on the first sub-track and in the second task we map with Snomed correctly 72% of the found entities.","PeriodicalId":338917,"journal":{"name":"Proceedings of The 5th Workshop on BioNLP Open Shared Tasks","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122600279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}