Medical Named Entity Recognition
13 papers with code • 2 benchmarks • 6 datasets
Benchmarks
These leaderboards are used to track progress in Medical Named Entity Recognition
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RadGraph
The QUAERO French Medical Corpus
Most implemented papers
BioBERT: a pre-trained biomedical language representation model for biomedical text mining
dmis-lab/biobert
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Biomedical text mining is becoming increasingly important as the number of biomedical documents rapidly grows.
SciBERT: A Pretrained Language Model for Scientific Text
allenai/scibert
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IJCNLP 2019
Obtaining large-scale annotated data for NLP tasks in the scientific domain is challenging and expensive.
Few-shot Learning for Named Entity Recognition in Medical Text
mxhofer/Named-Entity-Recognition-BidirectionalLSTM-CNN-CoNLL
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Deep neural network models have recently achieved state-of-the-art performance gains in a variety of natural language processing (NLP) tasks (Young, Hazarika, Poria, & Cambria, 2017).
Med7: a transferable clinical natural language processing model for electronic health records
In this work we introduced a named-entity recognition model for clinical natural language processing.
Embedding Transfer for Low-Resource Medical Named Entity Recognition: A Case Study on Patient Mobility
drgriffis/NeuralVecmap
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WS 2018
Functioning is gaining recognition as an important indicator of global health, but remains under-studied in medical natural language processing research.
A Neural Multi-Task Learning Framework to Jointly Model Medical Named Entity Recognition and Normalization
SendongZhao/Multi-Task-Learning-for-MER-and-MEN
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State-of-the-art studies have demonstrated the superiority of joint modelling over pipeline implementation for medical named entity recognition and normalization due to the mutual benefits between the two processes.
BioFLAIR: Pretrained Pooled Contextualized Embeddings for Biomedical Sequence Labeling Tasks
We also investigate the effects of a small amount of additional pretraining on PubMed content, and of combining FLAIR and ELMO models.
Biomedical Named Entity Recognition at Scale
Named entity recognition (NER) is a widely applicable natural language processing task and building block of question answering, topic modeling, information retrieval, etc.
ELECTRAMed: a new pre-trained language representation model for biomedical NLP
The overwhelming amount of biomedical scientific texts calls for the development of effective language models able to tackle a wide range of biomedical natural language processing (NLP) tasks.
