SOTAVerified

Clinical Concept Extraction

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

( Source )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 11–20 of 24 papers

TitleStatusHype
GatorTron: A Large Clinical Language Model to Unlock Patient Information from Unstructured Electronic Health Records—0
Identifying Risk Factors For Heart Disease in Electronic Medical Records: A Deep Learning Approach—0
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
ThinkMiners: Disorder Recognition using Conditional Random Fields and Distributional Semantics—0
Analysis of Word Embeddings and Sequence Features for Clinical Information Extraction—0
Clinical Concept Extraction: a Methodology Review—0
BURExtract-Llama: An LLM for Clinical Concept Extraction in Breast Ultrasound Reports—0
CliNER 2.0: Accessible and Accurate Clinical Concept Extraction—0
Show:102550
← PrevPage 2 of 3Next →

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