The objective of this paper is to discuss why Bayesian statistics is not used more in healthcare decision making and what might be done to increase the use of Bayesian methods. First, a case is made for why Bayesian analysis should be used more widely. Serious weaknesses of commonly used frequentist methods are discussed and contrasted with advantages of Bayesian methods. Next, the question of ...

objectives due to the lack of a standard tool for assessing patients’ capacity to consent to medical treatment in iran, the present study was carried out aiming to devise a persian version of a cross-cultural adaptation of the macarthur competence assessment tool. conclusions in the present study, we are able to focus on and prove the efficacy and benefits of this measurement tool. results the ...

Bayesian statistics has become a popular framework in various fields of experimental psychology such as signal detection theory, speech recognition, cue integration and decision making. However, it is still an open question how the human brain actually incorporates this functionality. One assumption is that the activities of populations of neurons encode probability distributions. Indeed, it ha...

The paper outlines a new challenging area of control, namely distributed decision making under uncertainty. Presence of many decision-making units, called the participants is the main distinction from the classical control theory. The problem is analysed from Bayesian point of view. Each participant has the abilities of classical adaptive controller, i.e. learning of the environment and design ...

We review two recent trends: the emergence of evidence-based medicine and the growing use of Bayesian statistics in medical applications. Evidence-based medicine requires an integrated assessment of the available evidence, and associated uncertainty, but there is also an emphasis on decision-making, for individual patients, or at other points in the health-care system. This demands consideratio...

When making a decision, one must first accumulate evidence, often over time, and then select the appropriate action. Here, we present a neural model of decision making that can perform both evidence accumulation and action selection optimally. More specifically, we show that, given a Poisson-like distribution of spike counts, biological neural networks can accumulate evidence without loss of in...

in this research, the decision on belief (dob) approach was employed to analyze and classify the states of uni-variate quality control systems. the concept of dob and its application in decision making problems were introduced, and then a methodology for modeling a statistical quality control problem by dob approach was discussed. for this iterative approach, the belief for a system being out-o...

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in recent decades, information technology systems and tools play an essential role in improving the method for responding the requests from managers. decision support system as an important tool has the fundamental role in organizations. in the team of software project allocating people to tasks has a noticeable effect on profits. a decision support system can help managers in making appropriat...