Papers with de-ID
Audio De-identification - a New Entity Recognition Task (N19-2)
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Ido Cohn, Itay Laish, Genady Beryozkin, Gang Li, Izhak Shafran, Idan Szpektor, Tzvika Hartman, Avinatan Hassidim, Yossi Matias
| Challenge: | Named Entity Recognition (NER) is an important step in de-identification (de-ID) of medical records, many of which are recorded conversations between a patient and a doctor. |
| Approach: | They propose to use Named Entity Recognition (NER) to detect audio spans with entity mentions in medical records and then use it to evaluate the results. |
| Outcome: | The proposed pipeline is based on a large labeled segment of the Switchboard and Fisher audio datasets and compares it with a benchmark. |
Generalizing Clinical De-identification Models by Privacy-safe Data Augmentation using GPT-4 (2024.emnlp-main)
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| Challenge: | De-identification (de-ID) is critical for patient confidentiality in clinical data management due to the difficulty of retaining training corpora and labeling standards vary across institutions. |
| Approach: | They propose to exploit GPT-4 for data augmentation through one-shot and zero-shot prompts to exploit the problem of PHI leakage by redacting PHI before processing. |
| Outcome: | The proposed approach significantly improves on three types of F1 scores in cross-dataset testing. |