SOTAVerified

Clinical Concept Extraction

Automatic extraction of clinical named entities such as clinical problems, treatments, tests and anatomical parts from clinical notes.

( Source )

Papers

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Showing 11–20 of 24 papers

TitleStatusHype
Machine-learned solutions for three stages of clinical information extraction: the state of the art at i2b2 2010—0
NLNDE at CANTEMIST: Neural Sequence Labeling and Parsing Approaches for Clinical Concept Extraction—0
Selective Attention Federated Learning: Improving Privacy and Efficiency for Clinical Text Classification—0
CliNER 2.0: Accessible and Accurate Clinical Concept Extraction—0
Clinical Concept and Relation Extraction Using Prompt-based Machine Reading Comprehension—0
Clinical Concept Extraction for Document-Level Coding—0
Cost-effective Selection of Pretraining Data: A Case Study of Pretraining BERT on Social Media—0
Bidirectional LSTM-CRF for Clinical Concept ExtractionCode0
Embedding Strategies for Specialized Domains: Application to Clinical Entity RecognitionCode0
Bidirectional LSTM-CRF for Clinical Concept ExtractionCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1BERTlarge (MIMIC)Exact Span F190.25—Unverified
2CharacterBERT (base, medical)Exact Span F189.24—Unverified
3ClinicalBERTExact Span F187.4—Unverified
4ELMo (finetuned on i2b2) + word2vec (i2b2)Exact Span F186.23—Unverified
5deBruijn et al. (System 1.1)Exact Span F185.23—Unverified