A privacy-preserving distributed filtering framework for NLP artifacts
2019
Background
Medical data sharing is a big challenge in biomedicine, which often hinders collaborative research. Due to privacy concerns, clinical notes cannot be directly shared. A lot of efforts have been dedicated to de-identifying clinical notes but it is still very challenging to accurately locate and scrub all sensitive elements from notes in an automatic manner. An alternative approach is to remove sentences that might contain sensitive terms related to personal information.
Keywords:
- Correction
- Source
- Cite
- Save
- Machine Reading By IdeaReader
45
References
10
Citations
NaN
KQI