1998
DOI: 10.1287/inte.28.4.64
|View full text |Cite
|
Sign up to set email alerts
|

Stochastic-Tree Models in Medical Decision Making

Abstract: Abstract:The stochastic tree is a recently introduced generalization of the decision tree which allows the explicit depiction of temporal uncertainty, while still employing the familiar rollback procedure for decision trees. We offer in this paper an introduction to stochastic tree modeling and techniques involved in their application to medical treatment decisions. We also describe an application of these tools to the analysis of the decision to undergo a total hip replacement from the perspectives of an indi… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

0
15
0

Year Published

1999
1999
2011
2011

Publication Types

Select...
6
3
1

Relationship

0
10

Authors

Journals

citations
Cited by 16 publications
(15 citation statements)
references
References 38 publications
0
15
0
Order By: Relevance
“…(Beccue 2001) Although in many cases, the role of theory in contextualization seems to be limited to ritual references, the content analysis suggests that it plays an important role as a normative guide. For instance, prior applications provide ideas for representing or modelling problems in specific domains of applications such as medical treatment (Hazen et al 1998). Prior academic knowledge is used to justify the appropriateness of structuring methodologies (Keeney 1999).…”
Section: Contextualizationmentioning
confidence: 99%
“…(Beccue 2001) Although in many cases, the role of theory in contextualization seems to be limited to ritual references, the content analysis suggests that it plays an important role as a normative guide. For instance, prior applications provide ideas for representing or modelling problems in specific domains of applications such as medical treatment (Hazen et al 1998). Prior academic knowledge is used to justify the appropriateness of structuring methodologies (Keeney 1999).…”
Section: Contextualizationmentioning
confidence: 99%
“…Decision trees are usually used for guidelines and are extensively used in CDSS. Examples can be found in (Critchfield & Willard, 1986;Hazen et al, 1998;Sonnenberg & Beck, 1993).…”
Section: Artificial Intelligencementioning
confidence: 99%
“…The use of discrete-time Markov chain models in medical decision applications dates back to the work of Beck and Pauker. 1 Hazen, [3][4][5] Hazen and Pellissier 6 and Hazen and others 7 have championed the use of continuous-time Markov chain models based on stochastic trees and have pointed out the mathematical convenience and simplicity of these models as long as the same rates are applied over a full lifetime. A discrete-time model can approximate a continuous-time Markov model by defining a cycle length of interest (for example, yearly or 6-month intervals).…”
Section: Markov Transition Models Are Frequently Used To Model Diseasmentioning
confidence: 99%