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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 1–50 of 174 papers

TitleStatusHype
Accurate clinical and biomedical Named entity recognition at scaleCode3
CheXpert Plus: Augmenting a Large Chest X-ray Dataset with Text Radiology Reports, Patient Demographics and Additional Image FormatsCode2
Radiology Text Analysis System (RadText): Architecture and EvaluationCode1
DeID-GPT: Zero-shot Medical Text De-Identification by GPT-4Code1
Synthesis of Realistic ECG using Generative Adversarial NetworksCode1
CIAGAN: Conditional Identity Anonymization Generative Adversarial NetworksCode1
Enhancing the De-identification of Personally Identifiable Information in Educational DataCode1
Hiding Visual Information via Obfuscating Adversarial PerturbationsCode1
EchoNet-Synthetic: Privacy-preserving Video Generation for Safe Medical Data SharingCode1
ESCOXLM-R: Multilingual Taxonomy-driven Pre-training for the Job Market DomainCode1
Few-Shot Cross-lingual Transfer for Coarse-grained De-identification of Code-Mixed Clinical TextsCode1
Speech Pseudonymisation Assessment Using Voice Similarity MatricesCode1
RiDDLE: Reversible and Diversified De-identification with Latent EncryptorCode1
De-Identification of Medical Imaging Data: A Comprehensive Tool for Ensuring Patient PrivacyCode1
DeID-VC: Speaker De-identification via Zero-shot Pseudo Voice ConversionCode1
The Text Anonymization Benchmark (TAB): A Dedicated Corpus and Evaluation Framework for Text AnonymizationCode1
Comparing Rule-based, Feature-based and Deep Neural Methods for De-identification of Dutch Medical RecordsCode1
MASK: A flexible framework to facilitate de-identification of clinical textsCode1
Reliable Generation of Privacy-preserving Synthetic Electronic Health Record Time Series via Diffusion ModelsCode1
Ego4D: Around the World in 3,000 Hours of Egocentric VideoCode1
Face Identity Disentanglement via Latent Space MappingCode1
SVIA: A Street View Image Anonymization Framework for Self-Driving ApplicationsCode0
Adversarial Learning of Privacy-Preserving Text Representations for De-Identification of Medical RecordsCode0
Biomedical Named Entity Recognition at ScaleCode0
Publicly Available Clinical BERT EmbeddingsCode0
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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