. Therapy planning is a very complex task, being the patient's therapeutic response affected by several sources of uncertainty. Furthermore, the modelling of a patient's evolution is frequently hampered by the incompleteness of the medical knowledge; it is hence often not possible to derive a mathematical model that is able to take into account the characteristics of the uncertain environment. An interesting way of coping with this class of problems is the Decision-Theoretic Planning approach, i.e. the formulations of policies on the basis of Decision Theory. This approach is able to provide plans in the presence of partial and qualitative information, while preserving a sound mathematical foundation. In this paper we will exploit...
Parameter uncertainty, patient heterogeneity, and stochastic uncertainty of outcomes are increasingl...
Abstract In oncology, decision-making in individual situations is often very complex. To deal with s...
As clinical decision making gets ever more complex, new analytical approaches are being developed to...
Decision making under uncertainty can be viewed as a planning task, because it basically amounts to ...
When a doctor is treating a patient, he is constantly facing decisions. From the externally visible ...
AbstractEffective handling of uncertainty is one of the central problems in medical decision making....
Decision-theoretic refinement planning is a new technique for finding optimal courses of action. The...
cisions are difficult because they are complex and have important consequences such as the impact on...
Graft-versus-host disease (GVHD) represents one of the major complications of allogeneic bone marrow...
We provide a tutorial on the construction and evalua-tion of Markov decision processes (MDPs), which...
How do people make difficult decisions in situations involving substantial risk and uncertainty? In ...
Health care providers face the problem of trying to make decisions with inadequate information and a...
This dissertation deals with decision support in the context of clinical oncology. (Dynamic) Bayesia...
Graphical models provide a powerful framework for reasoning under uncertainty, and an influence diag...
AbstractBecause decision modeling involves the construction of an explicit, mathematically describab...
Parameter uncertainty, patient heterogeneity, and stochastic uncertainty of outcomes are increasingl...
Abstract In oncology, decision-making in individual situations is often very complex. To deal with s...
As clinical decision making gets ever more complex, new analytical approaches are being developed to...
Decision making under uncertainty can be viewed as a planning task, because it basically amounts to ...
When a doctor is treating a patient, he is constantly facing decisions. From the externally visible ...
AbstractEffective handling of uncertainty is one of the central problems in medical decision making....
Decision-theoretic refinement planning is a new technique for finding optimal courses of action. The...
cisions are difficult because they are complex and have important consequences such as the impact on...
Graft-versus-host disease (GVHD) represents one of the major complications of allogeneic bone marrow...
We provide a tutorial on the construction and evalua-tion of Markov decision processes (MDPs), which...
How do people make difficult decisions in situations involving substantial risk and uncertainty? In ...
Health care providers face the problem of trying to make decisions with inadequate information and a...
This dissertation deals with decision support in the context of clinical oncology. (Dynamic) Bayesia...
Graphical models provide a powerful framework for reasoning under uncertainty, and an influence diag...
AbstractBecause decision modeling involves the construction of an explicit, mathematically describab...
Parameter uncertainty, patient heterogeneity, and stochastic uncertainty of outcomes are increasingl...
Abstract In oncology, decision-making in individual situations is often very complex. To deal with s...
As clinical decision making gets ever more complex, new analytical approaches are being developed to...