SOTAVerified

De-identification

De-identification is the task of detecting privacy-related entities in text, such as person names, emails and contact data.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1–50 of 174 papers

TitleStatusHype
Accurate clinical and biomedical Named entity recognition at scaleCode3
CheXpert Plus: Augmenting a Large Chest X-ray Dataset with Text Radiology Reports, Patient Demographics and Additional Image FormatsCode2
Enhancing the De-identification of Personally Identifiable Information in Educational DataCode1
De-Identification of Medical Imaging Data: A Comprehensive Tool for Ensuring Patient PrivacyCode1
EchoNet-Synthetic: Privacy-preserving Video Generation for Safe Medical Data SharingCode1
Reliable Generation of Privacy-preserving Synthetic Electronic Health Record Time Series via Diffusion ModelsCode1
ESCOXLM-R: Multilingual Taxonomy-driven Pre-training for the Job Market DomainCode1
DeID-GPT: Zero-shot Medical Text De-Identification by GPT-4Code1
RiDDLE: Reversible and Diversified De-identification with Latent EncryptorCode1
Hiding Visual Information via Obfuscating Adversarial PerturbationsCode1
DeID-VC: Speaker De-identification via Zero-shot Pseudo Voice ConversionCode1
Few-Shot Cross-lingual Transfer for Coarse-grained De-identification of Code-Mixed Clinical TextsCode1
Radiology Text Analysis System (RadText): Architecture and EvaluationCode1
The Text Anonymization Benchmark (TAB): A Dedicated Corpus and Evaluation Framework for Text AnonymizationCode1
Ego4D: Around the World in 3,000 Hours of Egocentric VideoCode1
Speech Pseudonymisation Assessment Using Voice Similarity MatricesCode1
MASK: A flexible framework to facilitate de-identification of clinical textsCode1
CIAGAN: Conditional Identity Anonymization Generative Adversarial NetworksCode1
Face Identity Disentanglement via Latent Space MappingCode1
Comparing Rule-based, Feature-based and Deep Neural Methods for De-identification of Dutch Medical RecordsCode1
Synthesis of Realistic ECG using Generative Adversarial NetworksCode1
Enhancing Clinical Models with Pseudo Data for De-identificationCode0
RedactOR: An LLM-Powered Framework for Automatic Clinical Data De-Identification—0
Re-identification of De-identified Documents with Autoregressive Infilling—0
Large Language Model Empowered Privacy-Protected Framework for PHI Annotation in Clinical Notes—0
Palmprint De-Identification Using Diffusion Model for High-Quality and Diverse Synthesis—0
Natural Language Processing for Electronic Health Records in Scandinavian Languages: Norwegian, Swedish, and Danish—0
Can Zero-Shot Commercial APIs Deliver Regulatory-Grade Clinical Text DeIdentification?—0
Antibiotic Resistance Microbiology Dataset (ARMD): A De-identified Resource for Studying Antimicrobial Resistance Using Electronic Health Records—0
Data-Constrained Synthesis of Training Data for De-Identification—0
Beyond De-Identification: A Structured Approach for Defining and Detecting Indirect Identifiers in Medical Texts—0
Zero-shot generation of synthetic neurosurgical data with large language modelsCode0
The Devil is in the Prompts: De-Identification Traces Enhance Memorization Risks in Synthetic Chest X-Ray GenerationCode0
SVIA: A Street View Image Anonymization Framework for Self-Driving ApplicationsCode0
Exploring AI-based System Design for Pixel-level Protected Health Information Detection in Medical Images—0
Medical Manifestation-Aware De-IdentificationCode0
LLMs-in-the-Loop Part 2: Expert Small AI Models for Anonymization and De-identification of PHI Across Multiple Languages—0
Face De-identification: State-of-the-art Methods and Comparative Studies—0
In-Context Learning for Preserving Patient Privacy: A Framework for Synthesizing Realistic Patient Portal MessagesCode0
Large Language Models for Patient Comments Multi-Label Classification—0
Low-Latency Video Anonymization for Crowd Anomaly Detection: Privacy vs. PerformanceCode0
DIRI: Adversarial Patient Reidentification with Large Language Models for Evaluating Clinical Text Anonymization—0
DeIDClinic: A Multi-Layered Framework for De-identification of Clinical Free-text DataCode0
Generating Synthetic Free-text Medical Records with Low Re-identification Risk using Masked Language ModelingCode0
Generation and De-Identification of Indian Clinical Discharge Summaries using LLMsCode0
Automated Privacy-Preserving Techniques via Meta-LearningCode0
GiusBERTo: A Legal Language Model for Personal Data De-identification in Italian Court of Auditors Decisions—0
AspirinSum: an Aspect-based utility-preserved de-identification Summarization framework—0
EALD-MLLM: Emotion Analysis in Long-sequential and De-identity videos with Multi-modal Large Language Model—0
Computational Job Market Analysis with Natural Language ProcessingCode0
Show:102550
← PrevPage 1 of 4Next →

No leaderboard results yet.