Leveraging network analysis to evaluate biomedical named entity recognition tools

Abstract The ever-growing availability of biomedical text sources has resulted in a boost in clinical studies based on their exploitation. Biomedical named-entity recognition (bio-NER) techniques have evolved remarkably in recent years and their application in research is increasingly successful. St...

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Autores principales:	Eduardo P. García del Valle, Gerardo Lagunes García, Lucía Prieto Santamaría, Massimiliano Zanin, Ernestina Menasalvas Ruiz, Alejandro Rodríguez-González
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/1a59a4ae3e8a47658867a982cc8edfda
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spelling	oai:doaj.org-article:1a59a4ae3e8a47658867a982cc8edfda2021-12-02T16:10:38ZLeveraging network analysis to evaluate biomedical named entity recognition tools10.1038/s41598-021-93018-w2045-2322https://doaj.org/article/1a59a4ae3e8a47658867a982cc8edfda2021-06-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-93018-whttps://doaj.org/toc/2045-2322Abstract The ever-growing availability of biomedical text sources has resulted in a boost in clinical studies based on their exploitation. Biomedical named-entity recognition (bio-NER) techniques have evolved remarkably in recent years and their application in research is increasingly successful. Still, the disparity of tools and the limited available validation resources are barriers preventing a wider diffusion, especially within clinical practice. We here propose the use of omics data and network analysis as an alternative for the assessment of bio-NER tools. Specifically, our method introduces quality criteria based on edge overlap and community detection. The application of these criteria to four bio-NER solutions yielded comparable results to strategies based on annotated corpora, without suffering from their limitations. Our approach can constitute a guide both for the selection of the best bio-NER tool given a specific task, and for the creation and validation of novel approaches.Eduardo P. García del ValleGerardo Lagunes GarcíaLucía Prieto SantamaríaMassimiliano ZaninErnestina Menasalvas RuizAlejandro Rodríguez-GonzálezNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-10 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Eduardo P. García del Valle Gerardo Lagunes García Lucía Prieto Santamaría Massimiliano Zanin Ernestina Menasalvas Ruiz Alejandro Rodríguez-González Leveraging network analysis to evaluate biomedical named entity recognition tools
description	Abstract The ever-growing availability of biomedical text sources has resulted in a boost in clinical studies based on their exploitation. Biomedical named-entity recognition (bio-NER) techniques have evolved remarkably in recent years and their application in research is increasingly successful. Still, the disparity of tools and the limited available validation resources are barriers preventing a wider diffusion, especially within clinical practice. We here propose the use of omics data and network analysis as an alternative for the assessment of bio-NER tools. Specifically, our method introduces quality criteria based on edge overlap and community detection. The application of these criteria to four bio-NER solutions yielded comparable results to strategies based on annotated corpora, without suffering from their limitations. Our approach can constitute a guide both for the selection of the best bio-NER tool given a specific task, and for the creation and validation of novel approaches.
format	article
author	Eduardo P. García del Valle Gerardo Lagunes García Lucía Prieto Santamaría Massimiliano Zanin Ernestina Menasalvas Ruiz Alejandro Rodríguez-González
author_facet	Eduardo P. García del Valle Gerardo Lagunes García Lucía Prieto Santamaría Massimiliano Zanin Ernestina Menasalvas Ruiz Alejandro Rodríguez-González
author_sort	Eduardo P. García del Valle
title	Leveraging network analysis to evaluate biomedical named entity recognition tools
title_short	Leveraging network analysis to evaluate biomedical named entity recognition tools
title_full	Leveraging network analysis to evaluate biomedical named entity recognition tools
title_fullStr	Leveraging network analysis to evaluate biomedical named entity recognition tools
title_full_unstemmed	Leveraging network analysis to evaluate biomedical named entity recognition tools
title_sort	leveraging network analysis to evaluate biomedical named entity recognition tools
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/1a59a4ae3e8a47658867a982cc8edfda
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_version_	1718384394447618048

Leveraging network analysis to evaluate biomedical named entity recognition tools

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