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http://hdl.handle.net/10773/29190
Title: | Clinical concept normalization on medical records using word embeddings and heuristics |
Author: | Silva, João Figueira Antunes, Rui Almeida, João Rafael Matos, Sérgio |
Keywords: | Natural language processing Clinical information extraction Clinical concept disambiguation Word embeddings Sieve-based model |
Issue Date: | 2020 |
Publisher: | IOS Press |
Abstract: | Electronic health records contain valuable information on patients' clinical history in the form of free text. Manually analyzing millions of these documents is unfeasible and automatic natural language processing methods are essential for efficiently exploiting these data. Within this, normalization of clinical entities, where the aim is to link entity mentions to reference vocabularies, is of utmost importance to successfully extract knowledge from clinical narratives. In this paper we present sieve-based models combined with heuristics and word embeddings and present results of our participation in the 2019 n2c2 (National NLP Clinical Challenges) shared-task on clinical concept normalization. |
Peer review: | yes |
URI: | http://hdl.handle.net/10773/29190 |
DOI: | 10.3233/SHTI200129 |
ISBN: | 978-1-64368-082-8 |
Appears in Collections: | DETI - Capítulo de livro IEETA - Capítulo de livro |
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