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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
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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