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A De-Identification Model for Korean Clinical Notes: Using Deep Learning Models
Junhyuk Chang, Jimyung Park, Chungsoo Kim, Rae Woong Park
1456 - 1457
10.3233/SHTI231242
Research Article
Studies in Health Technology and Informatics
Volume 310: MEDINFO 2023 — The Future Is Accessible
Abstract

To extract information from free-text in clinical records due to the patient’s protected health information PHI in the records pre-processing of de-identification is required. Therefore we aimed to identify PHI list and fine-tune the deep learning BERT model for developing de-identification model. The result of fine-tuning the model is strict F1 score of 0.924. Due to the convinced score the model can be used for the development of a de-identification model.

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