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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 41–50 of 174 papers

TitleStatusHype
An Analysis Of Protected Health Information Leakage In Deep-Learning Based De-Identification Algorithms—0
Data-Constrained Synthesis of Training Data for De-Identification—0
DeepDefacer: Automatic Removal of Facial Features via U-Net Image Segmentation—0
Deepfakes for Medical Video De-Identification: Privacy Protection and Diagnostic Information Preservation—0
Deep Learning Architecture for Patient Data De-identification in Clinical Records—0
An Easy-to-use and Robust Approach for the Differentially Private De-Identification of Clinical Textual Documents—0
Cross-Clinic De-Identification of Swedish Electronic Health Records: Nuances and Caveats—0
De-identification is not always enough—0
De-Identification of Clinical Free Text in Dutch with Limited Training Data: A Case Study—0
Audio De-identification: A New Entity Recognition Task—0
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