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Negation Detection

Negation detection is the task of identifying negation cues in text.

Papers

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Showing 1–25 of 55 papers

TitleStatusHype
Radiology Text Analysis System (RadText): Architecture and EvaluationCode1
Not a cute stroke: Analysis of Rule- and Neural Network-based Information Extraction Systems for Brain Radiology ReportsCode1
Clinical Text Summarization with Syntax-Based Negation and Semantic Concept IdentificationCode1
HPI-DHC at TREC 2018 Precision Medicine TrackCode1
ReXVQA: A Large-scale Visual Question Answering Benchmark for Generalist Chest X-ray Understanding—0
Beyond Negation Detection: Comprehensive Assertion Detection Models for Clinical NLP—0
Revisiting subword tokenization: A case study on affixal negation in large language models—0
Effective Matching of Patients to Clinical Trials using Entity Extraction and Neural Re-ranking—0
A negation detection assessment of GPTs: analysis with the xNot360 dataset—0
A Semantic Approach to Negation Detection and Word Disambiguation with Natural Language Processing—0
Negation detection in Dutch clinical texts: an evaluation of rule-based and machine learning methodsCode0
Negation Detection in Dutch Spoken Human-Computer Conversations—0
Improving negation detection with negation-focused pre-training—0
Improving negation detection with negation-focused pre-training—0
Flat and Nested Negation and Uncertainty Detection with PubMed BERT—0
NADE: A Benchmark for Robust Adverse Drug Events Extraction in Face of NegationsCode0
Scope resolution of predicted negation cues: A two-step neural network-based approach—0
MedAI at SemEval-2021 Task 10: Negation-aware Pre-training for Source-free Negation Detection Domain Adaptation—0
The University of Arizona at SemEval-2021 Task 10: Applying Self-training, Active Learning and Data Augmentation to Source-free Domain Adaptation—0
SemEval-2021 Task 10: Source-Free Domain Adaptation for Semantic ProcessingCode0
IITK at SemEval-2021 Task 10: Source-Free Unsupervised Domain Adaptation using Class Prototypes—0
EntityBERT: Entity-centric Masking Strategy for Model Pretraining for the Clinical Domain—0
Negation typology and general representation models for cross-lingual zero-shot negation scope resolution in Russian, French, and Spanish.—0
Domain adaptation in practice: Lessons from a real-world information extraction pipeline—0
Automatic Extraction of Ranked SNP-Phenotype Associations from Literature through Detecting Neural Candidates, Negation and Modality Markers—0
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