University of Illinois Urbana-Champaign

Detecting Privacy-Sensitive Events in Medical Text

Jindal, Prateek; Roth, Dan; Gunter, Carl A.

Content Files
prateekSHARP.pdf

Permalink

https://hdl.handle.net/2142/45819

Description

Title
Detecting Privacy-Sensitive Events in Medical Text
Author(s)
  • Jindal, Prateek
  • Roth, Dan
  • Gunter, Carl A.
Issue Date
2013-09-24
Keyword(s)
  • Natural Language Processing (NLP)
  • Electronic Health Records
  • Mention Detection
  • Set-Expansion
  • SNOMED CT
Date of Ingest
2013-09-24T15:07:26Z
Abstract
Recent US government initiatives have led to wide adoption of Electronic Health Records (EHRs). More and more health care institutions are storing patients' data in an electronic format. This emerging practice is posing several security-related risks because electronic data can easily be shared within and across institutions. So, it is important to design robust frameworks which will protect patients' privacy. In this report, we present a method to detect security-related (particularly drug abuse) events in medical text. Several applications can use this information to make the hospital systems more secure. For example, portions of the clinical reports which contain description of critical events can be encrypted so that it can be viewed only by selected individuals.
Type of Resource
text
Genre of Resource
Technical Report
Language
en
Permalink
http://hdl.handle.net/2142/45819
Sponsor(s)/Grant Number(s)
HHS 90TR0003/01
Copyright and License Information
Copyright 2013 Prateek Jindal

Owning Collections

Research and Tech Reports - Computer Science PRIMARY