Using FHIR to Construct a Corpus of Clinical Questions Annotated with Logical Forms and Answers.
AMIA Annu Symp Proc
; 2019: 1207-1215, 2019.
Article
em En
| MEDLINE
| ID: mdl-32308918
ABSTRACT
This paper describes a novel technique for annotating logical forms and answers for clinical questions by utilizing Fast Healthcare Interoperability Resources (FHIR). Such annotations are widely used in building the semantic parsing models (which aim at understanding the precise meaning of natural language questions by converting them to machine-understandable logical forms). These systems focus on reducing the time it takes for a user to get to information present in electronic health records (EHRs). Directly annotating questions with logical forms is a challenging task and involves a time-consuming step of concept normalization annotation. We aim to automate this step using the normalized codes present in a FHIR resource. Using the proposed approach, two annotators curated an annotated dataset of 1000 questions in less than 1 week. To assess the quality of these annotations, we trained a semantic parsing model which achieved an accuracy of 94.2% on this corpus.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Processamento de Linguagem Natural
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Registros Eletrônicos de Saúde
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Curadoria de Dados
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Interoperabilidade da Informação em Saúde
Tipo de estudo:
Prognostic_studies
Limite:
Humans
Idioma:
En
Ano de publicação:
2019
Tipo de documento:
Article