Leveraging network analysis to evaluate biomedical named entity recognition tools

Author:

García del Valle Eduardo P.,Lagunes García Gerardo,Prieto Santamaría Lucía,Zanin Massimiliano,Menasalvas Ruiz Ernestina,Rodríguez-González Alejandro

Abstract

AbstractThe 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.

Funder

Consejo Nacional de Ciencia y Tecnología

Comunidad de Madrid

Horizon 2020 Framework Programme

Agencia Estatal de Investigación

Publisher

Springer Science and Business Media LLC

Subject

Multidisciplinary

Reference47 articles.

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