De-identification of patient notes with recurrent neural networks
Objective: Patient notes in electronic health records (EHRs) may contain critical information for medical investigations. However, the vast majority of medical investigators can only access de-identified notes, in order to protect the confidentiality of patients. In the United States, the Health Ins...
Główni autorzy: | Dernoncourt, Franck, Lee, Ji Young, Uzuner, Ozlem, Szolovits, Peter |
---|---|
Kolejni autorzy: | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science |
Format: | Artykuł |
Język: | en_US |
Wydane: |
BMJ Publishing Group
2017
|
Dostęp online: | http://hdl.handle.net/1721.1/111064 https://orcid.org/0000-0002-1119-1346 https://orcid.org/0000-0001-6887-0924 https://orcid.org/0000-0001-8411-6403 |
Podobne zapisy
-
Transfer learning for named-entity recognition with neural networks
od: Lee, Ji Young, i wsp.
Wydane: (2020) -
Neural Networks for Joint Sentence Classification in Medical Paper Abstracts
od: Dernoncourt, Franck, i wsp.
Wydane: (2020) -
NeuroNER: an easy-to-use program for named-entity recognition based on neural networks
od: Dernoncourt, Franck, i wsp.
Wydane: (2021) -
NeuroNER: an easy-to-use program for named-entity recognition based on neural networks
od: Dernoncourt, Franck, i wsp.
Wydane: (2022) -
MIT at SemEval-2017 task 10: relation extraction with convolutional neural networks
od: Lee, Ji Young, i wsp.
Wydane: (2020)