Extracting BI-RADS Features from Portuguese Clinical Texts.

Nassif, Houssam; Cunha, Filipe; Moreira, Inês C; Cruz-Correia, Ricardo; Sousa, Eliana; Page, David; Burnside, Elizabeth; Dutra, Inês

Nassif, Houssam; Cunha, Filipe; Moreira, Inês C; Cruz-Correia, Ricardo; Sousa, Eliana; Page, David; Burnside, Elizabeth; Dutra, Inês.

Afiliación

Nassif H; University of Wisconsin, Madison, USA ( nassif@wisc.edu ).

Proceedings (IEEE Int Conf Bioinformatics Biomed) ; : 1-4, 2012.

Article en En | MEDLINE | ID: mdl-23797461

RESUMEN

In this work we build the first BI-RADS parser for Portuguese free texts, modeled after existing approaches to extract BI-RADS features from English medical records. Our concept finder uses a semantic grammar based on the BIRADS lexicon and on iterative transferred expert knowledge. We compare the performance of our algorithm to manual annotation by a specialist in mammography. Our results show that our parser's performance is comparable to the manual method.

Palabras clave

BI-RADS descriptors; breast cancer; feature extraction

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Proceedings (IEEE Int Conf Bioinformatics Biomed) Año: 2012 Tipo del documento: Article Pais de publicación: Estados Unidos

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