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The Benefits of Using a Complete Probability Distribution when Decision Making: An Example in Anticoagulant Drug Therapy |
Carney, Michael; Cunningham, Padraig
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TCD-CS-2005-58 In this paper we aim to show how probabilistic prediction of
a continuous variable could be more beneficial to a medical practitioner
than classification or numeric/point prediction of the same variable in
many scenarios. We introduce a probability density forecasting model
that produces accurate estimates and achieves statistically consistent
predicted distributions. An empirical evaluation of this approach on the
problem of warfarin dosage prediction is described and a comparison of
results obtained from our probabilistic models with a number of classification techniques on this problem is also shown.
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Keyword(s):
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Computer Science |
Publication Date:
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2005 |
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Type:
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Report |
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Peer-Reviewed:
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Unknown |
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Language(s):
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English |
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Institution:
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Trinity College Dublin |
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Citation(s):
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Carney, Michael; Cunningham, Padraig. 'The Benefits of Using a Complete Probability Distribution when Decision Making: An Example in Anticoagulant Drug Therapy'. - Dublin, Trinity College Dublin, Department of Computer Science, TCD-CS-2005-58, 2005, pp22 |
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Publisher(s):
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Trinity College Dublin, Department of Computer Science |
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File Format(s):
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application/pdf |
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First Indexed:
2014-05-13 05:31:10 Last Updated:
2015-04-10 05:13:50 |
