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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 101–150 of 174 papers

TitleStatusHype
FICGAN: Facial Identity Controllable GAN for De-identification—0
De-identification of Unstructured Clinical Texts from Sequence to Sequence Perspective—0
A Systematical Solution for Face De-identification—0
Dutch Named Entity Recognition and De-identification Methods for the Human Resource Domain—0
CFA-Net: Controllable Face Anonymization Network with Identity Representation Manipulation—0
De-identification of Privacy-related Entities in Job PostingsCode0
rx-anon -- A Novel Approach on the De-Identification of Heterogeneous Data based on a Modified Mondrian Algorithm—0
Creating and Evaluating a Synthetic Norwegian Clinical Corpus for De-Identification—0
Applying and Sharing pre-trained BERT-models for Named Entity Recognition and Classification in Swedish Electronic Patient Records—0
HB Deid - HB De-identification tool demonstrator—0
Benchmarking Modern Named Entity Recognition Techniques for Free-text Health Record De-identification—0
Differentially Private Imaging via Latent Space Manipulation—0
IdentityDP: Differential Private Identification Protection for Face Images—0
Performance of Automatic De-identification Across Different Note Types—0
Transferability of Neural Network Clinical De-identification Systems—0
A Context-Enhanced De-identification System—0
An Analysis Of Protected Health Information Leakage In Deep-Learning Based De-Identification Algorithms—0
Fidelity and Privacy of Synthetic Medical Data—0
Personalized and Invertible Face De-Identification by Disentangled Identity Information Manipulation—0
Adversarial Privacy Preservation in MRI Scans of the Brain—0
De-identifying Australian Hospital Discharge Summaries: An End-to-End Framework using Ensemble of Deep Learning Models—0
Biomedical Named Entity Recognition at ScaleCode0
Speaker De-identification System using Autoencodersand Adversarial Training—0
The Multilingual Anonymisation Toolkit for Public Administrations (MAPA) Project—0
The Impact of De-identification on Downstream Named Entity Recognition in Clinical Text—0
PHICON: Improving Generalization of Clinical Text De-identification Models via Data AugmentationCode0
Smartphone Camera De-identification while Preserving Biometric Utility—0
Privacy Guarantees for De-identifying Text TransformationsCode0
Hide-and-Seek Privacy ChallengeCode0
The UU-Net: Reversible Face De-Identification for Visual Surveillance Video FootageCode0
NLNDE: The Neither-Language-Nor-Domain-Experts' Way of Spanish Medical Document De-Identification—0
D\'esidentification de donn\'ees texte produites dans un cadre de relation client (De-identification of customer relationship text data )—0
Closing the Gap: Joint De-Identification and Concept Extraction in the Clinical DomainCode0
A Semi-supervised Approach for De-identification of Swedish Clinical Text—0
CodE Alltag 2.0 --- A Pseudonymized German-Language Email Corpus—0
Deepfakes for Medical Video De-Identification: Privacy Protection and Diagnostic Information Preservation—0
Live Face De-Identification in Video—0
Building a De-identification System for Real Swedish Clinical Text Using Pseudonymised Clinical Text—0
Towards De-identification of Legal Texts—0
De-Identification of Emails: Pseudonymizing Privacy-Sensitive Data in a German Email Corpus—0
Augmenting a De-identification System for Swedish Clinical Text Using Open Resources and Deep Learning—0
Feature Robustness in Non-stationary Health Records: Caveats to Deployable Model Performance in Common Clinical Machine Learning TasksCode0
KU\_ai at MEDIQA 2019: Domain-specific Pre-training and Transfer Learning for Medical NLI—0
Reversible Privacy Preservation using Multi-level Encryption and Compressive Sensing—0
Scrubbing Sensitive PHI Data from Medical Records made Easy by SpaCy -- A Scalable Model Implementation Comparisons—0
Adversarial Learning of Privacy-Preserving Text Representations for De-Identification of Medical RecordsCode0
Audio De-identification - a New Entity Recognition Task—0
Towards Automatic Generation of Shareable Synthetic Clinical Notes Using Neural Language ModelsCode0
AnonymousNet: Natural Face De-Identification with Measurable Privacy—0
Publicly Available Clinical BERT EmbeddingsCode0
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