Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/99340
Title: Modelling medical decisions in DynaMoL: a new general framework of dynamic decision analysis.
Authors: Leong, T.Y. 
Cao, C. 
Issue Date: 1998
Citation: Leong, T.Y.,Cao, C. (1998). Modelling medical decisions in DynaMoL: a new general framework of dynamic decision analysis.. Medinfo. MEDINFO 9 Pt 1 : 483-487. ScholarBank@NUS Repository.
Abstract: Dynamic decision analysis concerns decision problems in which both time and uncertainty are explicitly considered. We present a new dynamic decision analysis framework, called DynamoL, that supports graphical presentation of the decision factors in multiple perspectives. To alleviate the difficulty in assessing conditional probabilities over time in dynamic decision models, DynaMoL incorporates a Bayesian learning system to automatically learn the probabilistic parameters from large medical databases. We describe the DynaMoL modeling and learning architecture through a medical decision problem on the optimal follow-up schedule for patients after curative colorectal cancer surgery. We also show that the modeling experience and results indicate practical promise for the framework.
Source Title: Medinfo. MEDINFO
URI: http://scholarbank.nus.edu.sg/handle/10635/99340
Appears in Collections:Staff Publications

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