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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 51–75 of 174 papers

TitleStatusHype
Privacy-preserving Optics for Enhancing Protection in Face De-identification—0
RID-TWIN: An end-to-end pipeline for automatic face de-identification in videosCode0
A Privacy-Preserving Unsupervised Speaker Disentanglement Method for Depression Detection from SpeechCode0
De-identification is not always enough—0
ToonerGAN: Reinforcing GANs for Obfuscating Automated Facial Indexing—0
SAIC: Integration of Speech Anonymization and Identity Classification—0
Beyond Accuracy: Automated De-Identification of Large Real-World Clinical Text Datasets—0
VerA: Versatile Anonymization Applicable to Clinical Facial Photographs—0
De-identification of clinical free text using natural language processing: A systematic review of current approaches—0
Disentangle Before Anonymize: A Two-stage Framework for Attribute-preserved and Occlusion-robust De-identification—0
Privacy Protection in MRI Scans Using 3D Masked Autoencoders—0
Generative Adversarial Networks for Dental Patient Identity Protection in Orthodontic Educational Imaging—0
Data-Driven but Privacy-Conscious: Pedestrian Dataset De-identification via Full-Body Person Synthesis—0
Fast refacing of MR images with a generative neural network lowers re-identification risk and preserves volumetric consistencyCode0
In the Name of Fairness: Assessing the Bias in Clinical Record De-identificationCode0
An Overview of AI and Blockchain Integration for Privacy-Preserving—0
Medical records condensation: a roadmap towards healthcare data democratisation—0
Sensitive Data Detection with High-Throughput Machine Learning Models in Electrical Health Records—0
Medical Image Deidentification, Cleaning and Compression Using Pylogik—0
PADME-SoSci: A Platform for Analytics and Distributed Machine Learning for the Social Sciences—0
Disguise without Disruption: Utility-Preserving Face De-Identification—0
Development and validation of a natural language processing algorithm to pseudonymize documents in the context of a clinical data warehouse—0
k-SALSA: k-anonymous synthetic averaging of retinal images via local style alignmentCode0
Report of the Medical Image De-Identification (MIDI) Task Group -- Best Practices and Recommendations—0
Pedestrian Attribute Editing for Gait Recognition and AnonymizationCode0
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