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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 131–140 of 174 papers

TitleStatusHype
An Overview of AI and Blockchain Integration for Privacy-Preserving—0
Antibiotic Resistance Microbiology Dataset (ARMD): A De-identified Resource for Studying Antimicrobial Resistance Using Electronic Health Records—0
Applying and Sharing pre-trained BERT-models for Named Entity Recognition and Classification in Swedish Electronic Patient Records—0
A Semi-supervised Approach for De-identification of Swedish Clinical Text—0
AspirinSum: an Aspect-based utility-preserved de-identification Summarization framework—0
A survey of automatic de-identification of longitudinal clinical narratives—0
A Systematical Solution for Face De-identification—0
Audio De-identification: A New Entity Recognition Task—0
Audio De-identification - a New Entity Recognition Task—0
Augmenting a De-identification System for Swedish Clinical Text Using Open Resources and Deep Learning—0
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