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Stochastic-Tree Models in Medical Decision Making
Author(s) -
Gordon B. Hazen,
James M. Pellissier,
Jayavel Sounderpandian
Publication year - 1998
Publication title -
informs journal on applied analytics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.662
H-Index - 64
eISSN - 1526-551X
pISSN - 0092-2102
DOI - 10.1287/inte.28.4.64
Subject(s) - decision tree , generalization , computer science , tree (set theory) , depiction , decision analysis , machine learning , operations research , artificial intelligence , data mining , mathematics , statistics , mathematical analysis , linguistics , philosophy
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 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 individual patient (via utility analysis) and of society (via cost-effectiveness analysis).

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