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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 51–60 of 174 papers

TitleStatusHype
An Overview of AI and Blockchain Integration for Privacy-Preserving—0
Medical records condensation: a roadmap towards healthcare data democratisation—0
Sensitive Data Detection with High-Throughput Machine Learning Models in Electrical Health Records—0
Medical Image Deidentification, Cleaning and Compression Using Pylogik—0
PADME-SoSci: A Platform for Analytics and Distributed Machine Learning for the Social Sciences—0
Disguise without Disruption: Utility-Preserving Face De-Identification—0
Development and validation of a natural language processing algorithm to pseudonymize documents in the context of a clinical data warehouse—0
DeID-GPT: Zero-shot Medical Text De-Identification by GPT-4Code1
k-SALSA: k-anonymous synthetic averaging of retinal images via local style alignmentCode0
Report of the Medical Image De-Identification (MIDI) Task Group -- Best Practices and Recommendations—0
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