ReviewJournal of biomedical informatics2023
An overview of biomedical entity linking throughout the years.
Review in Journal of biomedical informatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
26 citing papers in PubMed.
- IID-KG: An ontology-aligned literature-derived knowledge graph for infectious and immune-mediated diseases.bioRxiv : the preprint server for biology · 2026Article
- Neuro-symbolic LLM Integration in Clinical Medicine: A Systematic Review and Taxonomy.Research square · 2026Article
- A practical and nuanced framework for entity linking evaluation.Journal of biomedical semantics · 2026Article
- Transformer-based relation extraction and concept normalization using an annotated clinical trials corpus.Scientific data · 2026Article
- Improving biomedical entity linking with generative relevance feedback.Bioinformatics (Oxford, England) · 2026Article
- Bangla MedER: Multi-BERT ensemble approach for the recognition of Bangla medical entity.PloS one · 2026Article
- Accurate Clinical Entity Recognition and Code Mapping of Anatomopathological Reports Using BioClinicalBERT Enhanced by Retrieval-Augmented Generation: A Hybrid Deep Learning Approach.Bioengineering (Basel, Switzerland) · 2025Article
- Exploring common data model coverage of nursing flowsheet data: a pilot study using SNOMED CT and LOINC mapping.JAMIA open · 2025Article
- DiMB-RE: mining the scientific literature for diet-microbiome associations.Journal of the American Medical Informatics Association : JAMIA · 2025Article
- High-precision information retrieval for rapid clinical guideline updates.NPJ digital medicine · 2025Article
- Improving Phenotyping of Patients With Immune-Mediated Inflammatory Diseases Through Automated Processing of Discharge Summaries: Multicenter Cohort Study.JMIR medical informatics · 2025Article
- Article
- A simplified retriever to improve accuracy of phenotype normalizations by large language models.Frontiers in digital health · 2025Article
- HunFlair2 in a cross-corpus evaluation of biomedical named entity recognition and normalization tools.Bioinformatics (Oxford, England) · 2024Article
- Integrating deep learning architectures for enhanced biomedical relation extraction: a pipeline approach.Database : the journal of biological databases and curation · 2024Article
- BELHD: improving biomedical entity linking with homonym disambiguation.Bioinformatics (Oxford, England) · 2024Article
- Multi-head CRF classifier for biomedical multi-class named entity recognition on Spanish clinical notes.Database : the journal of biological databases and curation · 2024Article
- Improving biomedical entity linking for complex entity mentions with LLM-based text simplification.Database : the journal of biological databases and curation · 2024Article
- Towards discovery: an end-to-end system for uncovering novel biomedical relations.Database : the journal of biological databases and curation · 2024Article
- A Dataset for Evaluating Contextualized Representation of Biomedical Concepts in Language Models.Scientific data · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.