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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 91–100 of 174 papers

TitleStatusHype
DeepDefacer: Automatic Removal of Facial Features via U-Net Image Segmentation—0
Utility Preservation of Clinical Text After De-Identification—0
Improving speaker de-identification with functional data analysis of f0 trajectoriesCode0
A Comparative Evaluation Of Transformer Models For De-Identification Of Clinical Text Data—0
Classifying Cyber-Risky Clinical Notes by Employing Natural Language Processing—0
Speaker Identification Experiments Under Gender De-Identification—0
Digital Speech Algorithms for Speaker De-Identification—0
Towards a Data Privacy-Predictive Performance Trade-off—0
Conditional De-Identification of 3D Magnetic Resonance Images—0
Named Entity Recognition in Unstructured Medical Text Documents—0
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