By Topic

Mining electronic medical records for patient care patterns

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Buczak, A.L. ; Johns Hopkins Univ. Appl. Phyiscs Lab., Laurel, MD ; Moniz, L.J. ; Feighner, B.H. ; Lombardo, J.S.

A novel approach for generating full Electronic Medical Records of synthetic victims is described. Special emphasis is put on the data mining steps that build patient care models and perform clustering of this highly dimensional data set. A methodology for cluster validation is proposed. Results for a large data set with Staphylococcus aureus and Methicillin-Resistant Staphylococcus aureus infections are presented.

Published in:

Computational Intelligence and Data Mining, 2009. CIDM '09. IEEE Symposium on

Date of Conference:

March 30 2009-April 2 2009