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Evaluating Medical Entity Recognition in Health Care: Entity Model Quantitative Study
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1 of the 55 references listed on this page is in the Retraction Watch database as retracted (export 2026-11-11): 10.1155/2022/3990563 (notice 2023-10-11).
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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inferredcites →https://doi.org/10.1162/dint_a_00105openalex-snapshot
Medical Named Entity Recognition from Un-labelled Medical Records based on Pre-trained Language Models and Domain Dictionary
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Various criteria in the evaluation of biomedical named entity recognition
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CollaboNet: collaboration of deep neural networks for biomedical named entity recognition
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Chinese Clinical Named Entity Recognition From Electronic Medical Records Based on Multisemantic Features by Using Robustly Optimized Bidirectional Encoder Representation From Transformers Pretraining Approach Whole Word Masking and Convolutional Neural Networks: Model Development and Validation
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Using the Natural Language Processing System Medical Named Entity Recognition-Japanese to Analyze Pharmaceutical Care Records: Natural Language Processing Analysis
inferredcites →https://doi.org/10.23919/fruct48808.2020.9087359openalex-snapshot
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inferredcites →https://doi.org/10.3390/healthcare11091268openalex-snapshot
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What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Entity–Relation Extraction from Chinese Medical Texts Based on Large Language Models and Data‑Augmentation Strategies
inferred← citeshttps://doi.org/10.1007/s00521-026-12324-4openalex-snapshot
The E6 model: span-level contrastive learning for enhancing biomedical named entity recognition
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inferred← citeshttps://doi.org/10.1109/icftic64248.2024.10912885openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/isaect68904.2025.11318790openalex-snapshot
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inferred← citeshttps://doi.org/10.2196/85825openalex-snapshot
Symptom Terminology Normalization in Traditional Chinese Medicine: Development and Evaluation of a 2-Stage Deep Learning Framework Based on Fine-Grained Semantic Classification
inferred← citeshttps://doi.org/10.2196/preprints.111552openalex-snapshot
Entity Recognition of the Age-Friendly Health System 4Ms in Nursing Home Text Messages Using Large Language Model Revision of Bio-ClinicalBERT Candidate Entities: Development and Evaluation Study (Preprint)
inferred← citeshttps://doi.org/10.2196/preprints.75561openalex-snapshot
Enhancing LLMs for Identifying and Prioritizing Important Medical Jargons from Electronic Health Record Notes Utilizing Data Augmentation (Preprint)
inferred← citeshttps://doi.org/10.3389/fdgth.2026.1758921openalex-snapshot
Recognition and linking of discontinuous named entities in healthcare: a comparative performance analysis
inferred← citeshttps://doi.org/10.3390/bioengineering13010030openalex-snapshot
Accurate Clinical Entity Recognition and Code Mapping of Anatomopathological Reports Using BioClinicalBERT Enhanced by Retrieval-Augmented Generation: A Hybrid Deep Learning Approach
inferred← citeshttps://doi.org/10.3390/electronics14183676openalex-snapshot
Enhancing Clinical Named Entity Recognition via Fine-Tuned BERT and Dictionary-Infused Retrieval-Augmented Generation
inferred← citeshttps://doi.org/10.4018/ijkm.372672openalex-snapshot
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