Papers with sanitizing electronic health records
Adversarial Learning of Privacy-Preserving Text Representations for De-Identification of Medical Records (P19-1)
Copied to clipboard
| Challenge: | De-identification is the task of detecting protected health information (PHI) in medical text. |
| Approach: | They propose to create shareable representations of medical text that contain no PHI and can be shared between organizations to create unified datasets for training de-identification models. |
| Outcome: | The proposed representation allows training a simple LSTM-CRF model to an F1 score of 97.4%. |