SOTAVerified

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 121–130 of 174 papers

TitleStatusHype
VerA: Versatile Anonymization Applicable to Clinical Facial Photographs—0
Language Resources to Support Language Diversity – the ELRA Achievements—0
Privacy Protection in MRI Scans Using 3D Masked Autoencoders—0
A Comparative Evaluation Of Transformer Models For De-Identification Of Clinical Text Data—0
A Context-Enhanced De-identification System—0
A Deep Learning Architecture for De-identification of Patient Notes: Implementation and Evaluation—0
Adversarial Privacy Preservation in MRI Scans of the Brain—0
Alternating Loss Correction for Preterm-Birth Prediction from EHR Data with Noisy Labels—0
An Analysis Of Protected Health Information Leakage In Deep-Learning Based De-Identification Algorithms—0
An Easy-to-use and Robust Approach for the Differentially Private De-Identification of Clinical Textual Documents—0
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