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Deidentifying a Norwegian clinical corpus - An effort to create a privacy-preserving Norwegian large clinical language model

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https://hdl.handle.net/10037/33415
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Date
2024
Type
Journal article
Tidsskriftartikkel
Peer reviewed

Author
Ngo, Phuong Dinh; Tejedor Hernandez, Miguel Angel; Olsen Svenning, Therese; Chomutare, Taridzo Fred; Budrionis, Andrius; Dalianis, Hercules
Abstract
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.
Description
Source at https://aclanthology.org/2024.caldpseudo-1.0.
Publisher
ACL
Citation
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). 2024
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