Tootfinder

Privacy-Aware, Public-Aligned: Embedding Risk Detection and Public Values into Scalable Clinical Text De-Identification for Trusted Research Environments
Arlene Casey, Stuart Dunbar, Franz Gruber, Samuel McInerney, Mat\'u\v{s} Falis, Pamela Linksted, Katie Wilde, Kathy Harrison, Alison Hamilton, Christian Cole
https://arxiv.…

Privacy-Aware, Public-Aligned: Embedding Risk Detection and Public Values into Scalable Clinical Text De-Identification for Trusted Research Environments
Clinical free-text data offers immense potential to improve population health research such as richer phenotyping, symptom tracking, and contextual understanding of patient care. However, these data present significant privacy risks due to the presence of directly or indirectly identifying information embedded in unstructured narratives. While numerous de-identification tools have been developed, few have been tested on real-world, heterogeneous datasets at scale or assessed for governance read…