Systematic Review of Named Entity Linking and Knowledge Organisation Systems in Biomedical and Clinical Domains

Knowledge and information in the biomedical domain are predominantly represented in text format and available in diverse sources, such as articles, patents, electronic health records, and social media. Automated approaches for organising these resources face significant challenges when understanding natural language. Knowledge organisation systems serve as a crucial standard for enhancing information retrieval and sharing among humans and automated approaches. Named entity linking plays a crucial role in bridging the gap between text and knowledge organisation systems: it maps relevant entities described in text, such as diseases, chemicals, and genes, to unambiguous entries in target knowledge organisation systems that accurately describe their meaning. In this review, we analysed 102 articles published between 2013 and 2024 related to named entity linking, which provides an overview of the landscape of knowledge organisation systems in the biomedical and clinical domains and of the evolution of this task over the past decade. The findings highlight key limitations of existing approaches and identify promising directions for future research.

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Journal
ACM Computing Surveys
Published
2026-02-12
DOI
https://doi.org/10.1145/3796222
Primary Topic
Biomedical Text Mining and Ontologies
Type
article
Field-Weighted Citation Impact
0.00
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article

Systematic Review of Named Entity Linking and Knowledge Organisation Systems in Biomedical and Clinical Domains

Pedro Ruas, Sofia I. R. Conceição, Francisco M. Couto
ACM Computing Surveys
Biomedical Text Mining and Ontologies
article

Systematic Review of Named Entity Linking and Knowledge Organisation Systems in Biomedical and Clinical Domains

Pedro Ruas, Sofia I. R. Conceição, Francisco M. Couto
article en

Abstract

Knowledge and information in the biomedical domain are predominantly represented in text format and available in diverse sources, such as articles, patents, electronic health records, and social media. Automated approaches for organising these resources face significant challenges when understanding natural language. Knowledge organisation systems serve as a crucial standard for enhancing information retrieval and sharing among humans and automated approaches. Named entity linking plays a crucial role in bridging the gap between text and knowledge organisation systems: it maps relevant entities described in text, such as diseases, chemicals, and genes, to unambiguous entries in target knowledge organisation systems that accurately describe their meaning. In this review, we analysed 102 articles published between 2013 and 2024 related to named entity linking, which provides an overview of the landscape of knowledge organisation systems in the biomedical and clinical domains and of the evolution of this task over the past decade. The findings highlight key limitations of existing approaches and identify promising directions for future research.

ACM Computing Surveys
University of Lisbon (PT)
Quality Education
Openalex Percentile: Top 58%
Biomedical Text Mining and Ontologies
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Systematic Review of Named Entity Linking and Knowledge Organisation Systems in Biomedical and Clinical Domains — Pedro Ruas, Sofia I. R. Conceição, et al. · ACM Computing Surveys (2026) | TGRS Research Map | TGRS