Imputation of missing values by integrating neural networks and case-based reasoning

Author

Ennett, Colleen M. ; Frize, Monique ; Walker, Robin C.

Author_Institution

Systems and Computer Engineering Department, Carleton University, Ottawa, ON, Canada

fYear

2008

fDate

20-25 Aug. 2008

Firstpage

4337

Lastpage

4341

Abstract

Missing values in a medical database present a problem when trying to develop a prediction model for a broad range of patients, if the data are not missing at random. We present a data imputation approach for physiologic parameters that incorporates individualized case information into the imputed values. We replaced missing values in a neonatal intensive care unit (NICU) database with relevant data by integrating aspects of artificial neural networks (ANNs) and case-based reasoning (CBR).

Keywords

Artificial neural networks; Blood; Databases; Gases; Laboratories; Neural networks; Pediatrics; Physiology; Predictive models; System testing; Artificial intelligence; case based reasoning; feed-forward neural networks; missing data; neonatal intensive care unit; Algorithms; Artificial Intelligence; Birth Weight; Computers; Data Interpretation, Statistical; Decision Support Systems, Clinical; Humans; Infant, Newborn; Intensive Care Units, Neonatal; Neural Networks (Computer); Research Design; Software;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 2008. EMBS 2008. 30th Annual International Conference of the IEEE

Conference_Location

Vancouver, BC

ISSN

1557-170X

Print_ISBN

978-1-4244-1814-5

Electronic_ISBN

1557-170X

Type

conf

DOI

10.1109/IEMBS.2008.4650170

Filename

4650170