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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 101–150 of 174 papers

TitleStatusHype
Smartphone Camera De-identification while Preserving Biometric Utility—0
Spanish Datasets for Sensitive Entity Detection in the Legal Domain—0
Speaker De-identification System using Autoencodersand Adversarial Training—0
Speaker Identification Experiments Under Gender De-Identification—0
StyleGAN as a Utility-Preserving Face De-identification Method—0
The Impact of De-identification on Downstream Named Entity Recognition in Clinical Text—0
The Multilingual Anonymisation Toolkit for Public Administrations (MAPA) Project—0
The NLP Sandbox: an efficient model-to-data system to enable federated and unbiased evaluation of clinical NLP models—0
ToonerGAN: Reinforcing GANs for Obfuscating Automated Facial Indexing—0
Toward Face Biometric De-identification using Adversarial Examples—0
Towards a Data Privacy-Predictive Performance Trade-off—0
Towards De-identification of Legal Texts—0
Towards Privacy-Preserving Person Re-identification via Person Identify Shift—0
Towards Reversible De-Identification in Video Sequences Using 3D Avatars and Steganography—0
Towards the Creation of a Large Corpus of Synthetically-Identified Clinical Notes—0
Transferability of Neural Network Clinical De-identification Systems—0
Transfer Learning for Named-Entity Recognition with Neural Networks—0
Using routinely collected patient data to support clinical trials research in accountable care organizations—0
Utility Preservation of Clinical Text After De-Identification—0
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
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
Automatic end-to-end De-identification: Is high accuracy the only metric?—0
Benchmarking Modern Named Entity Recognition Techniques for Free-text Health Record De-identification—0
Beyond Accuracy: Automated De-Identification of Large Real-World Clinical Text Datasets—0
Beyond De-Identification: A Structured Approach for Defining and Detecting Indirect Identifiers in Medical Texts—0
Building a De-identification System for Real Swedish Clinical Text Using Pseudonymised Clinical Text—0
Can Zero-Shot Commercial APIs Deliver Regulatory-Grade Clinical Text DeIdentification?—0
Classifying Cyber-Risky Clinical Notes by Employing Natural Language Processing—0
CodE Alltag 2.0 --- A Pseudonymized German-Language Email Corpus—0
Conditional De-Identification of 3D Magnetic Resonance Images—0
Creating and Evaluating a Synthetic Norwegian Clinical Corpus for De-Identification—0
Cross-Clinic De-Identification of Swedish Electronic Health Records: Nuances and Caveats—0
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