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Application of the Weka Machine Learning Library to Hospital Ward Occupancy Problems

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Author
Harris, Ian
Denzinger, Joerg
Yergens, Dean
Accessioned
2008-02-27T16:59:13Z
Available
2008-02-27T16:59:13Z
Computerscience
2008-01-04
Issued
2008-01-04
Subject
Computer Science
Type
unknown
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Abstract
We explore the potential of applying machine learning techniques to the management of patient ow in hospitals. For this project, we have obtained the Weka machine learning library and three years of historical ward occupancy data from Rockyview Hospital. We use Weka's classifier algorithms and the Rockyview data to build a model of patient ow through each ward. Using Weka, we then attempt to predict ward occupancy problems on any given day using the model and the ward conditions from the previous day. This process is repeated for all eighteen wards. Finally, we obtain rules (sets of ward conditions that warn of an impending occupancy problem) for each ward and present the results.
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We are currently acquiring citations for the work deposited into this collection. We recognize the distribution rights of this item may have been assigned to another entity, other than the author(s) of the work.If you can provide the citation for this work or you think you own the distribution rights to this work please contact the Institutional Repository Administrator at digitize@ucalgary.ca
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University of Calgary
Faculty
Science
Doi
http://dx.doi.org/10.11575/PRISM/30573
Uri
http://hdl.handle.net/1880/45853
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