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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 76–100 of 174 papers

TitleStatusHype
Large Language Models for Patient Comments Multi-Label Classification—0
Live Face De-Identification in Video—0
LLMs-in-the-Loop Part 2: Expert Small AI Models for Anonymization and De-identification of PHI Across Multiple Languages—0
MAPA Project: Ready-to-Go Open-Source Datasets and Deep Learning Technology to Remove Identifying Information from Text Documents—0
Medical Image Deidentification, Cleaning and Compression Using Pylogik—0
Named Entity Recognition in Unstructured Medical Text Documents—0
Natural Language Processing for Electronic Health Records in Scandinavian Languages: Norwegian, Swedish, and Danish—0
NLNDE: The Neither-Language-Nor-Domain-Experts' Way of Spanish Medical Document De-Identification—0
Open video data sharing in developmental and behavioural science—0
PADME-SoSci: A Platform for Analytics and Distributed Machine Learning for the Social Sciences—0
Palmprint De-Identification Using Diffusion Model for High-Quality and Diverse Synthesis—0
Performance of Automatic De-identification Across Different Note Types—0
Personalized and Invertible Face De-Identification by Disentangled Identity Information Manipulation—0
Plausible Deniability for Privacy-Preserving Data Synthesis—0
Privacy-preserving Optics for Enhancing Protection in Face De-identification—0
Privacy-Protective-GAN for Face De-identification—0
Privacy-Utility Balanced Voice De-Identification Using Adversarial Examples—0
RedactOR: An LLM-Powered Framework for Automatic Clinical Data De-Identification—0
Re-identification of De-identified Documents with Autoregressive Infilling—0
Report of the Medical Image De-Identification (MIDI) Task Group -- Best Practices and Recommendations—0
Reversible Privacy Preservation using Multi-level Encryption and Compressive Sensing—0
rx-anon -- A Novel Approach on the De-Identification of Heterogeneous Data based on a Modified Mondrian Algorithm—0
SAIC: Integration of Speech Anonymization and Identity Classification—0
Scrubbing Sensitive PHI Data from Medical Records made Easy by SpaCy -- A Scalable Model Implementation Comparisons—0
Sensitive Data Detection with High-Throughput Machine Learning Models in Electrical Health Records—0
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