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Multi-Level Representation Learning for Chinese Medical Entity Recognition: Model Development and Validation

https://doi.org/10.2196/17637
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/s10796-019-09932-yopenalex-snapshot
TL-NER: A Transfer Learning Model for Chinese Named Entity Recognition
inferredcites →https://doi.org/10.1016/j.jbi.2015.05.009openalex-snapshot
Annotating risk factors for heart disease in clinical narratives for diabetic patients
inferredcites →https://doi.org/10.1162/tacl_a_00051openalex-snapshot
Enriching Word Vectors with Subword Information
inferredcites →https://doi.org/10.1186/s12911-019-0762-7openalex-snapshot
A deep learning model incorporating part of speech and self-matching attention for named entity recognition of Chinese electronic medical records
inferredcites →https://doi.org/10.18653/v1/d16-1153openalex-snapshot
Phonologically Aware Neural Model for Named Entity Recognition in Low Resource Transfer Settings
inferredcites →https://doi.org/10.18653/v1/d17-1018openalex-snapshot
End-to-end Neural Coreference Resolution
inferredcites →https://doi.org/10.18653/v1/d18-1179openalex-snapshot
Dissecting Contextual Word Embeddings: Architecture and Representation
inferredcites →https://doi.org/10.18653/v1/d18-1489openalex-snapshot
Direct Output Connection for a High-Rank Language Model
inferredcites →https://doi.org/10.18653/v1/n16-1030openalex-snapshot
Neural Architectures for Named Entity Recognition
inferredcites →https://doi.org/10.18653/v1/n18-1131openalex-snapshot
A Neural Layered Model for Nested Named Entity Recognition
inferredcites →https://doi.org/10.18653/v1/n18-1202openalex-snapshot
Deep Contextualized Word Representations
inferredcites →https://doi.org/10.18653/v1/n18-2056openalex-snapshot
Improve Neural Entity Recognition via Multi-Task Data Selection and Constrained Decoding
inferredcites →https://doi.org/10.18653/v1/p16-1101openalex-snapshot
End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF
inferredcites →https://doi.org/10.18653/v1/p17-1110openalex-snapshot
Adversarial Multi-Criteria Learning for Chinese Word Segmentation
inferredcites →https://doi.org/10.18653/v1/p19-2041openalex-snapshot
Embedding Strategies for Specialized Domains: Application to Clinical Entity Recognition
inferredcites →https://doi.org/10.2196/14850openalex-snapshot
Combining Contextualized Embeddings and Prior Knowledge for Clinical Named Entity Recognition: Evaluation Study
inferredcites →https://doi.org/10.3115/v1/d14-1162openalex-snapshot
Glove: Global Vectors for Word Representation
inferredcites →https://doi.org/10.3233/978-1-61499-564-7-624openalex-snapshot
Named Entity Recognition in Chinese Clinical Text Using Deep Neural Network

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/s00417-025-07035-wopenalex-snapshot
Clinical parameters associated with blood pressure in patients with primary open-angle glaucoma and exfoliation glaucoma
inferred← citeshttps://doi.org/10.1016/j.artmed.2024.102822openalex-snapshot
Automatic quantitative stroke severity assessment based on Chinese clinical named entity recognition with domain-adaptive pre-trained large language model
inferred← citeshttps://doi.org/10.1016/j.asoc.2021.107358openalex-snapshot
Adversarial transfer network with bilinear attention for the detection of adverse drug reactions from social media
inferred← citeshttps://doi.org/10.1055/s-0041-1726528openalex-snapshot
Year 2020 (with COVID): Observation of Scientific Literature on Clinical Natural Language Processing
inferred← citeshttps://doi.org/10.1109/icitee49829.2020.9271752openalex-snapshot
Domain-Specific Contextualized Embedding: A Systematic Literature Review
inferred← citeshttps://doi.org/10.1109/psgai68158.2025.11413537openalex-snapshot
CSAT-Former: A Cross-Scale Aligned Transformer for Hierarchical Wind Power Forecasting with Temporal Consistency
inferred← citeshttps://doi.org/10.1186/s12911-025-03257-4openalex-snapshot
A framework for normalized extraction of fine-grained traditional Chinese medicine symptom entities and relations
inferred← citeshttps://doi.org/10.2196/23898openalex-snapshot
Health Natural Language Processing: Methodology Development and Applications
inferred← citeshttps://doi.org/10.2196/54580openalex-snapshot
An Entity Extraction Pipeline for Medical Text Records Using Large Language Models: Analytical Study
inferred← citeshttps://doi.org/10.2196/preprints.23898openalex-snapshot
Health Natural Language Processing: Methodology Development and Applications (Preprint)
inferred← citeshttps://doi.org/10.2196/preprints.71208openalex-snapshot
Co-morbidity and co-symptom network analysis of diabetes EMR based on Bi-LSTM-CRF entity extraction framework (Preprint)
inferred← citeshttps://doi.org/10.3934/mbe.2022640openalex-snapshot
Disease prediction based on multi-type data fusion from Chinese electronic health record
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