DMCA
The benefits of using a complete probability distribution when decision making: an example in anticoagulant drug therapy. Medical Decision Making (forthcoming
| Citations: | 1 - 0 self |
BibTeX
@MISC{Carney_thebenefits,
author = {Michael Carney and Padraig Cunningham and Stephen Byrne},
title = {The benefits of using a complete probability distribution when decision making: an example in anticoagulant drug therapy. Medical Decision Making (forthcoming},
year = {}
}
Share
 |
 |
 |
 |
||
OpenURL
Abstract
Abstract. 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. 1
Keyphrases
medical decision making complete probability distribution decision making anticoagulant drug therapy classification technique accurate estimate probabilistic model probabilistic prediction medical practitioner warfarin dosage prediction continuous variable many scenario numeric point prediction probability density empirical evaluation
