Healthcare Data Mining: Prediction Inpatient Length of Stay

Data mining approaches have been widely applied in the field of healthcare. At the same time it is recognized that most healthcare datasets are full of missing values. In this paper we apply decision trees, Naive Bayesian classifiers and feature selection methods to a geriatric hospital dataset in o...

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Bibliographic Details
Published in:2006 3rd International IEEE Conference Intelligent Systems 2006-09, p.832-837
Main Authors: Peng Liu, Lei Lei, Junjie Yin, Wei Zhang, Wu Naijun, El-Darzi, E.
Format: Article
Language:English
Subjects:
Bayesian methods
Classification tree analysis
Data mining
Decision trees
Healthcare data mining
Hospitals
Intelligent systems
Learning systems
LOS
Medical services
NBI
Niobium compounds
Robustness
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Summary:Data mining approaches have been widely applied in the field of healthcare. At the same time it is recognized that most healthcare datasets are full of missing values. In this paper we apply decision trees, Naive Bayesian classifiers and feature selection methods to a geriatric hospital dataset in order to predict inpatient length of stay, especially for the long stay patients
ISSN:1541-1672
1941-1294
DOI:10.1109/IS.2006.348528