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 61–70 of 174 papers

TitleStatusHype
Applying and Sharing pre-trained BERT-models for Named Entity Recognition and Classification in Swedish Electronic Patient Records—0
De-identification of medical records using conditional random fields and long short-term memory networks—0
Beyond De-Identification: A Structured Approach for Defining and Detecting Indirect Identifiers in Medical Texts—0
De-Identification of French Unstructured Clinical Notes for Machine Learning Tasks—0
De-Identification of Emails: Pseudonymizing Privacy-Sensitive Data in a German Email Corpus—0
Beyond Accuracy: Automated De-Identification of Large Real-World Clinical Text Datasets—0
Antibiotic Resistance Microbiology Dataset (ARMD): A De-identified Resource for Studying Antimicrobial Resistance Using Electronic Health Records—0
De-identification of clinical free text using natural language processing: A systematic review of current approaches—0
De-Identification of Clinical Free Text in Dutch with Limited Training Data: A Case Study—0
Benchmarking Modern Named Entity Recognition Techniques for Free-text Health Record De-identification—0
Show:102550
← PrevPage 7 of 18Next →

No leaderboard results yet.