Abstract In the present paper we discussed the parameters optimization in medical decision making using maximum entropy weight. Currently, most medical decision models rely on point estimates for input parameters, although the uncertainty surrounding these values is well-recognized. However, it still left some challenge problems that are commonly involved in computational problems involving exp...

This paper presents a tutorial introduction to the handling of uncertainty and decision-making in medical reasoning systems. It focuses on the central role of uncertainty in all of medicine and identifies the major themes that arise in research papers. It then reviews simple Bayesian formulations of the problem and pursues the generalization to the Bayesian network methods that are popular toda...

We develop a new framework for designing online policies given access to an oracle providing statistical information about off-line benchmark. Having such prediction oracles enables simple and natural Bayesian selection raises the question as how these perform in different settings. Our work makes two important contributions toward this question: First, we general technique call compensated cou...

Within decision theory the use of Bayesian methodology is well established. However, primarily due to complexity problems the use in applied Decision Support Systems within animal production has been very limited. Recently, methodological developments have removed many of these problems, and the time seems to be ripe for wide-scale applications. Bayesian methods handles decision making under un...

one of the methods used in the analysis of data related to diseases, and their underlying reasons is drawing geographical map. mapping diseases is a valuable tool to determine the regions of high rate of infliction requiring therapeutic interventions. the objective of this study was to investigate obesity pattern in iran by drawing geographical maps based on bayesian spatial model to recognize ...

The method of Bond Graph based Analytical Redundancy Relations in Fault Detection and Isolation is explicitly associated with components faults, this is due to architectural and functional aspect of the Bond Graph tool. This allows using the reliability of each component to improve the decision-making step. The purpose of this paper is the improvement of the classical binary method of decision-...