MASK: A flexible framework to facilitate de-identification of clinical texts

05/24/2020
by   Nikola Milosevic, et al.
0

Medical health records and clinical summaries contain a vast amount of important information in textual form that can help advancing research on treatments, drugs and public health. However, the majority of these information is not shared because they contain private information about patients, their families, or medical staff treating them. Regulations such as HIPPA in the US, PHIPPA in Canada and GDPR regulate the protection, processing and distribution of this information. In case this information is de-identified and personal information are replaced or redacted, they could be distributed to the research community. In this paper, we present MASK, a software package that is designed to perform the de-identification task. The software is able to perform named entity recognition using some of the state-of-the-art techniques and then mask or redact recognized entities. The user is able to select named entity recognition algorithm (currently implemented are two versions of CRF-based techniques and BiLSTM-based neural network with pre-trained GLoVe and ELMo embedding) and masking algorithm (e.g. shift dates, replace names/locations, totally redact entity).

READ FULL TEXT

page 1

page 2

page 3

page 4

research
04/08/2020

Entity-Switched Datasets: An Approach to Auditing the In-Domain Robustness of Named Entity Recognition Models

Named entity recognition systems perform well on standard datasets compr...
research
03/25/2021

Benchmarking Modern Named Entity Recognition Techniques for Free-text Health Record De-identification

Electronic Health Records (EHRs) have become the primary form of medical...
research
07/07/2020

An Emergency Medical Services Clinical Audit System driven by Named Entity Recognition from Deep Learning

Clinical performance audits are routinely performed in Emergency Medical...
research
09/06/2019

#MeTooMaastricht: Building a chatbot to assist survivors of sexual harassment

Inspired by the recent social movement of #MeToo, we are building a chat...
research
06/27/2023

CamemBERT-bio: a Tasty French Language Model Better for your Health

Clinical data in hospitals are increasingly accessible for research thro...
research
01/01/2021

De-identifying Hospital Discharge Summaries: An End-to-End Framework using Ensemble of De-Identifiers

Objective:Electronic Medical Records (EMRs) contain clinical narrative t...
research
05/04/2021

Automatic de-identification of Data Download Packages

The General Data Protection Regulation (GDPR) grants all natural persons...

Please sign up or login with your details

Forgot password? Click here to reset