Deidentifying a Norwegian clinical corpus - An effort to create a privacy-preserving Norwegian large clinical language model
Permanent lenke
https://hdl.handle.net/10037/33415Dato
2024Type
Journal articleTidsskriftartikkel
Peer reviewed
Forfatter
Ngo, Phuong Dinh; Tejedor Hernandez, Miguel Angel; Olsen Svenning, Therese; Chomutare, Taridzo Fred; Budrionis, Andrius; Dalianis, HerculesSammendrag
This study discusses the methods and challenges of deidentifying and pseudonymizing Norwegian clinical text for research purposes. The results of the NorDeid tool for deidentification and pseudonymization on different types of protected health information were evaluated and discussed, as well as the extension of its functionality with regular expressions to identify specific types of sensitive information. This research used a clinical corpus of adult patients treated in a gastro-surgical department in Norway, which contains approximately nine million clinical notes. The study also highlights the challenges posed by the unique language and clinical terminology of Norway and emphasizes the importance of protecting privacy and the need for customized approaches to meet legal and research requirements.
Beskrivelse
Source at https://aclanthology.org/2024.caldpseudo-1.0.
Forlag
ACLSitering
Ngo, Tejedor Hernandez, Olsen Svenning, Chomutare, Budrionis, Dalianis. Deidentifying a Norwegian clinical corpus - An effort to create a privacy-preserving Norwegian large clinical language model. Proceedings of the Workshop on Computational Approaches to Language Data Pseudonymization (CALD-pseudo 2024). 2024Metadata
Vis full innførselSamlinger
Copyright 2024 The Author(s)