A keyphrase-based approach for interpretable ICD-10 code classification of Spanish medical reports

Duque, Andrés, Fabregat, Hermenegildo, Araujo, Lourdes y Martinez-Romo, Juan . (2021) A keyphrase-based approach for interpretable ICD-10 code classification of Spanish medical reports. Artificial Intelligence in Medicine 102177

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Título A keyphrase-based approach for interpretable ICD-10 code classification of Spanish medical reports
Autor(es) Duque, Andrés
Fabregat, Hermenegildo
Araujo, Lourdes
Martinez-Romo, Juan
Materia(s) Biomedicina
Ingeniería Informática
Abstract Background and objectives: The 10th version of International Classification of Diseases (ICD-10) codification system has been widely adopted by the health systems of many countries, including Spain. However, manual code assignment of Electronic Health Records (EHR) is a complex and time-consuming task that requires a great amount of specialised human resources. Therefore, several machine learning approaches are being proposed to assist in the assignment task. In this work we present an alternative system for automatically recommending ICD-10 codes to be assigned to EHRs. Methods: Our proposal is based on characterising ICD-10 codes by a set of keyphrases that represent them. These keyphrases do not only include those that have literally appeared in some EHR with the considered ICD-10 codes assigned, but also others that have been obtained by a statistical process able to capture expressions that have led the annotators to assign the code. Results: The result is an information model that allows to efficiently recommend codes to a new EHR based on their textual content. We explore an approach that proves to be competitive with other state-of-the-art approaches and can be combined with them to optimise results. Conclusions: In addition to its effectiveness, the recommendations of this method are easily interpretable since the phrases in an EHR leading to recommend an ICD-10 code are known. Moreover, the keyphrases associated with each ICD-10 code can be a valuable additional source of information for other approaches, such as machine learning techniques.
Palabras clave Medical records
ICD-10 codes
Keyphrase extraction
Interpretability
Editor(es) Elsevier
Fecha 2021
Formato application/pdf
Identificador bibliuned:DptoLSI-ETSI-Articulos-Aduque-0002
http://e-spacio.uned.es/fez/view/bibliuned:DptoLSI-ETSI-Articulos-Aduque-0002
DOI - identifier https://doi.org/10.1016/j.artmed.2021.102177
ISSN - identifier 0933-3657
Nombre de la revista Artificial Intelligence in Medicine
Número de Volumen 121
Publicado en la Revista Artificial Intelligence in Medicine 102177
Idioma eng
Versión de la publicación publishedVersion
Tipo de recurso Article
Derechos de acceso y licencia http://creativecommons.org/licenses/by-nc-nd/4.0
info:eu-repo/semantics/openAccess
Tipo de acceso Acceso abierto
Notas adicionales La versión registrada de este artículo, publicado por primera vez en Artificial Intelligence in Medicine (2021) 121 102177, está disponible en línea en el sitio web del editor: Elsevier, https://doi.org/10.1016/j.artmed.2021.102177
Notas adicionales The registered version of this article, first published in Artificial Intelligence in Medicine (2021) 121 102177, is available online at the publisher's website: Elsevier, https://doi.org/10.1016/j.artmed.2021.102177

 
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Creado: Fri, 22 Mar 2024, 21:39:22 CET