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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 111–120 of 174 papers

TitleStatusHype
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
De-identifying Australian Hospital Discharge Summaries: An End-to-End Framework using Ensemble of Deep Learning Models—0
Adversarial Privacy Preservation in MRI Scans of the Brain—0
Biomedical Named Entity Recognition at ScaleCode0
Speaker De-identification System using Autoencodersand Adversarial Training—0
The Impact of De-identification on Downstream Named Entity Recognition in Clinical Text—0
The Multilingual Anonymisation Toolkit for Public Administrations (MAPA) Project—0
PHICON: Improving Generalization of Clinical Text De-identification Models via Data AugmentationCode0
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