An annotated corpus with nanomedicine and pharmacokinetic parameters

Nastassja A Lewinski,1 Ivan Jimenez,1 Bridget T McInnes2 1Department of Chemical and Life Science Engineering, Virginia Commonwealth University, Richmond, VA, 2Department of Computer Science, Virginia Commonwealth University, Richmond, VA, USA Abstract: A vast amount of data on nanomedicines is be...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Lewinski NA, Jimenez I, McInnes BT
Formato:	article
Lenguaje:	EN
Publicado:	Dove Medical Press 2017
Materias:	nanotechnology informatics natural language processing text mining corpora Medicine (General) R5-920
Acceso en línea:	https://doaj.org/article/2447f3a9c96c488ea56374487aaec32b
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:2447f3a9c96c488ea56374487aaec32b
record_format	dspace
spelling	oai:doaj.org-article:2447f3a9c96c488ea56374487aaec32b2021-12-02T03:11:39ZAn annotated corpus with nanomedicine and pharmacokinetic parameters1178-2013https://doaj.org/article/2447f3a9c96c488ea56374487aaec32b2017-10-01T00:00:00Zhttps://www.dovepress.com/an-annotated-corpus-with-nanomedicine-and-pharmacokinetic-parameters-peer-reviewed-article-IJNhttps://doaj.org/toc/1178-2013Nastassja A Lewinski,1 Ivan Jimenez,1 Bridget T McInnes2 1Department of Chemical and Life Science Engineering, Virginia Commonwealth University, Richmond, VA, 2Department of Computer Science, Virginia Commonwealth University, Richmond, VA, USA Abstract: A vast amount of data on nanomedicines is being generated and published, and natural language processing (NLP) approaches can automate the extraction of unstructured text-based data. Annotated corpora are a key resource for NLP and information extraction methods which employ machine learning. Although corpora are available for pharmaceuticals, resources for nanomedicines and nanotechnology are still limited. To foster nanotechnology text mining (NanoNLP) efforts, we have constructed a corpus of annotated drug product inserts taken from the US Food and Drug Administration’s Drugs@FDA online database. In this work, we present the development of the Engineered Nanomedicine Database corpus to support the evaluation of nanomedicine entity extraction. The data were manually annotated for 21 entity mentions consisting of nanomedicine physicochemical characterization, exposure, and biologic response information of 41 Food and Drug Administration-approved nanomedicines. We evaluate the reliability of the manual annotations and demonstrate the use of the corpus by evaluating two state-of-the-art named entity extraction systems, OpenNLP and Stanford NER. The annotated corpus is available open source and, based on these results, guidelines and suggestions for future development of additional nanomedicine corpora are provided. Keywords: nanotechnology, informatics, natural language processing, text mining, corporaLewinski NAJimenez IMcInnes BTDove Medical Pressarticlenanotechnologyinformaticsnatural language processingtext miningcorporaMedicine (General)R5-920ENInternational Journal of Nanomedicine, Vol Volume 12, Pp 7519-7527 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	nanotechnology informatics natural language processing text mining corpora Medicine (General) R5-920
spellingShingle	nanotechnology informatics natural language processing text mining corpora Medicine (General) R5-920 Lewinski NA Jimenez I McInnes BT An annotated corpus with nanomedicine and pharmacokinetic parameters
description	Nastassja A Lewinski,1 Ivan Jimenez,1 Bridget T McInnes2 1Department of Chemical and Life Science Engineering, Virginia Commonwealth University, Richmond, VA, 2Department of Computer Science, Virginia Commonwealth University, Richmond, VA, USA Abstract: A vast amount of data on nanomedicines is being generated and published, and natural language processing (NLP) approaches can automate the extraction of unstructured text-based data. Annotated corpora are a key resource for NLP and information extraction methods which employ machine learning. Although corpora are available for pharmaceuticals, resources for nanomedicines and nanotechnology are still limited. To foster nanotechnology text mining (NanoNLP) efforts, we have constructed a corpus of annotated drug product inserts taken from the US Food and Drug Administration’s Drugs@FDA online database. In this work, we present the development of the Engineered Nanomedicine Database corpus to support the evaluation of nanomedicine entity extraction. The data were manually annotated for 21 entity mentions consisting of nanomedicine physicochemical characterization, exposure, and biologic response information of 41 Food and Drug Administration-approved nanomedicines. We evaluate the reliability of the manual annotations and demonstrate the use of the corpus by evaluating two state-of-the-art named entity extraction systems, OpenNLP and Stanford NER. The annotated corpus is available open source and, based on these results, guidelines and suggestions for future development of additional nanomedicine corpora are provided. Keywords: nanotechnology, informatics, natural language processing, text mining, corpora
format	article
author	Lewinski NA Jimenez I McInnes BT
author_facet	Lewinski NA Jimenez I McInnes BT
author_sort	Lewinski NA
title	An annotated corpus with nanomedicine and pharmacokinetic parameters
title_short	An annotated corpus with nanomedicine and pharmacokinetic parameters
title_full	An annotated corpus with nanomedicine and pharmacokinetic parameters
title_fullStr	An annotated corpus with nanomedicine and pharmacokinetic parameters
title_full_unstemmed	An annotated corpus with nanomedicine and pharmacokinetic parameters
title_sort	annotated corpus with nanomedicine and pharmacokinetic parameters
publisher	Dove Medical Press
publishDate	2017
url	https://doaj.org/article/2447f3a9c96c488ea56374487aaec32b
work_keys_str_mv	AT lewinskina anannotatedcorpuswithnanomedicineandpharmacokineticparameters AT jimenezi anannotatedcorpuswithnanomedicineandpharmacokineticparameters AT mcinnesbt anannotatedcorpuswithnanomedicineandpharmacokineticparameters AT lewinskina annotatedcorpuswithnanomedicineandpharmacokineticparameters AT jimenezi annotatedcorpuswithnanomedicineandpharmacokineticparameters AT mcinnesbt annotatedcorpuswithnanomedicineandpharmacokineticparameters
_version_	1718401841724653568

An annotated corpus with nanomedicine and pharmacokinetic parameters

Ejemplares similares