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An overview of biomedical entity linking throughout the years

https://doi.org/10.1016/j.jbi.2022.104252

French, Evan; McInnes, Bridget T. (January 2023, Journal of Biomedical Informatics)

Biomedical Entity Linking (BEL) is the task of mapping of spans of text within biomedical documents to normalized, unique identifiers within an ontology. This is an important task in natural language processing for both translational information extraction applications and providing context for downstream tasks like relationship extraction. In this paper, we will survey the progression of BEL from its inception in the late 80s to present day state of the art systems, provide a comprehensive list of datasets available for training BEL systems, reference shared tasks focused on BEL, discuss the technical components that comprise BEL systems, and discuss possible directions for the future of the field.
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Effects of data and entity ablation on multitask learning models for biomedical entity recognition

https://doi.org/10.1016/j.jbi.2022.104062

Rodriguez, Nicholas E.; Nguyen, Mai; McInnes, Bridget T. (June 2022, Journal of Biomedical Informatics)

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Exploring Representations for Singular and Multi-Concept Relations for Biomedical Named Entity Normalization

https://doi.org/10.1145/3487553.3524701

Cuffy, Clint; French, Evan; Fehrmann, Sophia; McInnes, Bridget T. (April 2022, WWW '22: Companion Proceedings of the Web Conference 2022)

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BioCreative VII-Track 1: A BERT-based System for Relation Extraction in Biomedical Text

Mahendran, Darshini; Ranjan, Sudhanshu; Tang, Jiawei; Nguyen, Mai; McInnes, Bridget T. (November 2021, BioCreative VII Workshop)

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Synthetic Biology Knowledge System

https://doi.org/10.1021/acssynbio.1c00188

Mante, Jeanet; Hao, Yikai; Jett, Jacob; Joshi, Udayan; Keating, Kevin; Lu, Xiang; Nakum, Gaurav; Rodriguez, Nicholas E.; Tang, Jiawei; Terry, Logan; et al (September 2021, ACS Synthetic Biology)
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