Title :
Mining electronic medical records for patient care patterns
Author :
Buczak, Anna L. ; Moniz, Linda J. ; Feighner, Brian H. ; Lombardo, Joseph S.
Author_Institution :
Johns Hopkins Univ. Appl. Phyiscs Lab., Laurel, MD
fDate :
March 30 2009-April 2 2009
Abstract :
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.
Keywords :
data mining; diseases; medical computing; medical information systems; patient care; pattern clustering; data mining; dimensional data set clustering; disease surveillance system; electronic medical record mining; patient care pattern model; synthetic victim; Control systems; Data mining; Diseases; Electronic equipment testing; Medical control systems; Medical tests; Sensitivity and specificity; Social network services; Surveillance; System testing;
Conference_Titel :
Computational Intelligence and Data Mining, 2009. CIDM '09. IEEE Symposium on
Conference_Location :
Nashville, TN
Print_ISBN :
978-1-4244-2765-9
DOI :
10.1109/CIDM.2009.4938642
