Biomedical Named Entity Recognition via Dictionary-based Synonym Generalization (2023.emnlp-main)
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| Challenge: | Existing methods for biomedical named entity recognition require laborious human effort. |
| Approach: | They propose a Synonym Generalization framework that recognizes biomedical concepts using span-based predictions. |
| Outcome: | The proposed framework outperforms dictionary-based approaches on a wide range of benchmarks. |
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| Challenge: | Biomedical named entities are often used as key features in biomedical text mining. |
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| Challenge: | Biomedical Concept Normalization (BCN) is widely used in biomedical text processing . despite numerous surface variants of biomedically-defined concepts, it remains challenging and unsolved. |
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| Challenge: | Generative methods for biomedical entity linking (EL) use synonyms knowledge from knowledge bases (KB) this is not trivial to inject into a generative method, but it is cost-effective. |
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Where do LLMs currently stand on biomedical NER in both clean and noisy settings ? (2026.findings-eacl)
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| Challenge: | despite advances in medicine, many diseases remain without effective treatments . clinical meta-analysis is essential for drug discovery and clinical research . |
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| Challenge: | Existing models for medical named entity recognition and named entity normalization suffer from error propagation between the two tasks. |
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| Challenge: | Named entity recognition (NER) is a task of identifying and classifying named entities (NE) within text. |
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A Generate-and-Rank Framework with Semantic Type Regularization for Biomedical Concept Normalization (2020.acl-main)
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| Challenge: | Concept normalization is a task that maps textual mentions of concepts to concepts in an ontology . lexical and grammatical variations are pervasive in such text, posing key challenges for data interoperability and the development of natural language processing (NLP) techniques. |
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| Challenge: | Named Entity Recognition (NER) and Relation Extraction (RE) are essential tools in distilling knowledge from biomedical literature. |
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OpenBioNER: Lightweight Open-Domain Biomedical Named Entity Recognition Through Entity Type Description (2025.findings-naacl)
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Alessio Cocchieri, Giacomo Frisoni, Marcos Martínez Galindo, Gianluca Moro, Giuseppe Tagliavini, Francesco Candoli
| Challenge: | Biomedical Named Entity Recognition (BioNER) is a computationally expensive and limited tool . specialized 7B NER LLMs and GPT-4o can't match textual spans with entity types . |
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