Building a De-identification System for Real Swedish Clinical Text Using Pseudonymised Clinical Text (D19-62)
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| Challenge: | Several ethical and scientific issues arise regarding the balance between maintaining patient confidentiality and the need for wider application of trained models. |
| Approach: | They propose to use pseudonymised clinical text as training data to de-identify real clinical text in other hospitals. |
| Outcome: | The proposed model performed better for some PHI information than the standard model and poor performance on Location and Health Care Unit information. |
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Kiana Aghakasiri, Noopur Zambare, JoAnn Thai, Carrie Ye, Mayur Mehta, J Ross Mitchell, Mohamed Abdalla
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| Challenge: | Automatic de-identification systems introduce errors due to their imperfect precision and may negatively impact the utility of the de-identified dataset. |
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