Please use this identifier to cite or link to this item:
|Title:||Constructing influence views from data to support dynamic decision making in medicine.|
|Authors:||Qi, X.Z. |
|Citation:||Qi, X.Z.,Leong, T.Y. (2001). Constructing influence views from data to support dynamic decision making in medicine.. Medinfo 10 (Pt 2) : 1389-1393. ScholarBank@NUS Repository.|
|Abstract:||A dynamic decision model can facilitate the complicated decision-making process in medicine, in which both time and uncertainty are explicitly considered. In this paper, we address the problem of automatic construction of a dynamic decision model from a large medical database. Within the DynaMoL (a dynamic decision modeling language) framework, a model can be represented in influence view. Thus, our proposed approach first learns the structures of the influence view based on the minimal description length (MDL) principle, and then obtains the conditional probabilities of the model by Bayesian method. The experiment results demonstrate that our system can efficiently construct the influence views from data with high fidelity.|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Feb 9, 2019
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.