Leveraging network analysis to evaluate biomedical named entity recognition tools
Eduardo P. García del Valle; Gerardo Lagunes García; Lucía Prieto Santamaría; Massimiliano Zanin; Ernestina Menasalvas Ruiz; Alejandro Rodríguez-González
Scientific Reports 11, 13537 (2021)
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.