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Mining electronic medical records for patient care patterns

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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

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