Miguel Tejedor


pdf bib
Deidentifying a Norwegian Clinical Corpus - an Effort to Create a Privacy-preserving Norwegian Large Clinical Language Model
Phuong Ngo | Miguel Tejedor | Therese Olsen Svenning | Taridzo Chomutare | Andrius Budrionis | Hercules Dalianis
Proceedings of the Workshop on Computational Approaches to Language Data Pseudonymization (CALD-pseudo 2024)

The 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. The 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.