SOTAVerified

De-identification

De-identification is the task of detecting privacy-related entities in text, such as person names, emails and contact data.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 26–50 of 174 papers

TitleStatusHype
Privacy Guarantees for De-identifying Text TransformationsCode0
Biomedical Named Entity Recognition at ScaleCode0
Adversarial Learning of Privacy-Preserving Text Representations for De-Identification of Medical RecordsCode0
Medical Manifestation-Aware De-IdentificationCode0
Natural Language Generation for Electronic Health RecordsCode0
Publicly Available Clinical BERT EmbeddingsCode0
In the Name of Fairness: Assessing the Bias in Clinical Record De-identificationCode0
In-Context Learning for Preserving Patient Privacy: A Framework for Synthesizing Realistic Patient Portal MessagesCode0
k-SALSA: k-anonymous synthetic averaging of retinal images via local style alignmentCode0
Generating Synthetic Free-text Medical Records with Low Re-identification Risk using Masked Language ModelingCode0
Feature Robustness in Non-stationary Health Records: Caveats to Deployable Model Performance in Common Clinical Machine Learning TasksCode0
Generation and De-Identification of Indian Clinical Discharge Summaries using LLMsCode0
Low-Latency Video Anonymization for Crowd Anomaly Detection: Privacy vs. PerformanceCode0
Enhancing Clinical Models with Pseudo Data for De-identificationCode0
Fast refacing of MR images with a generative neural network lowers re-identification risk and preserves volumetric consistencyCode0
Computational Job Market Analysis with Natural Language ProcessingCode0
DEDUCE: A pattern matching method for automatic de-identification of Dutch medical textCode0
Hide-and-Seek Privacy ChallengeCode0
Improving speaker de-identification with functional data analysis of f0 trajectoriesCode0
Automated Privacy-Preserving Techniques via Meta-LearningCode0
DeIDClinic: A Multi-Layered Framework for De-identification of Clinical Free-text DataCode0
De-identification of Privacy-related Entities in Job PostingsCode0
Closing the Gap: Joint De-Identification and Concept Extraction in the Clinical DomainCode0
PHICON: Improving Generalization of Clinical Text De-identification Models via Data AugmentationCode0
De-identification of Patient Notes with Recurrent Neural NetworksCode0
Show:102550
← PrevPage 2 of 7Next →

No leaderboard results yet.