A privacy-preserving distributed filtering framework for NLP artifacts

A privacy-preserving distributed filtering framework for NLP artifacts

Abstract 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 accurat...

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Bibliographic Details
Main Authors: Md Nazmus Sadat, Md Momin Al Aziz, Noman Mohammed, Serguei Pakhomov, Hongfang Liu, Xiaoqian Jiang
Format: Article
Language:English
Published: BMC 2019-09-01
Series:BMC Medical Informatics and Decision Making
Subjects:
Biomedical data security and privacy
Clinical notes de-identification
Homomorphic encryption
Online Access:http://link.springer.com/article/10.1186/s12911-019-0867-z

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http://link.springer.com/article/10.1186/s12911-019-0867-z

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