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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 71–80 of 174 papers

TitleStatusHype
Digital Speech Algorithms for Speaker De-Identification—0
Downstream Task Performance of BERT Models Pre-Trained Using Automatically De-Identified Clinical Data—0
Dutch Named Entity Recognition and De-identification Methods for the Human Resource Domain—0
EALD-MLLM: Emotion Analysis in Long-sequential and De-identity videos with Multi-modal Large Language Model—0
AspirinSum: an Aspect-based utility-preserved de-identification Summarization framework—0
Adversarial Privacy Preservation in MRI Scans of the Brain—0
End-to-end speech recognition modeling from de-identified data—0
Creating and Evaluating a Synthetic Norwegian Clinical Corpus for De-Identification—0
Differentially Private Imaging via Latent Space Manipulation—0
Development and validation of a natural language processing algorithm to pseudonymize documents in the context of a clinical data warehouse—0
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