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De-identification

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

Papers

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Showing 26–50 of 174 papers

TitleStatusHype
PHICON: Improving Generalization of Clinical Text De-identification Models via Data AugmentationCode0
Medical Manifestation-Aware De-IdentificationCode0
Privacy Guarantees for De-identifying Text TransformationsCode0
A Privacy-Preserving Unsupervised Speaker Disentanglement Method for Depression Detection from SpeechCode0
RID-TWIN: An end-to-end pipeline for automatic face de-identification in videosCode0
The Devil is in the Prompts: De-Identification Traces Enhance Memorization Risks in Synthetic Chest X-Ray GenerationCode0
In-Context Learning for Preserving Patient Privacy: A Framework for Synthesizing Realistic Patient Portal MessagesCode0
Improving speaker de-identification with functional data analysis of f0 trajectoriesCode0
In the Name of Fairness: Assessing the Bias in Clinical Record De-identificationCode0
Pedestrian Attribute Editing for Gait Recognition and AnonymizationCode0
Feature Robustness in Non-stationary Health Records: Caveats to Deployable Model Performance in Common Clinical Machine Learning TasksCode0
Generating Synthetic Free-text Medical Records with Low Re-identification Risk using Masked Language ModelingCode0
k-SALSA: k-anonymous synthetic averaging of retinal images via local style alignmentCode0
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
Generation and De-Identification of Indian Clinical Discharge Summaries using LLMsCode0
Hide-and-Seek Privacy ChallengeCode0
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
Natural Language Generation for Electronic Health RecordsCode0
De-identification of Patient Notes with Recurrent Neural NetworksCode0
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