Add to ORKGRelative entropy is a concept within information theory that provides a measure of the distance between two probability distributions. The author proposes that the amount of information gained by performing a diagnostic test can be quantified by calculating the relative entropy between the posttest and pretest probability distributions. This statistic, in essence, quantifies the degree to which the results of a diagnostic test are likely to reduce our surprise upon ultimately learning a patient’s diagnosis. A previously proposed measure of diagnostic information that is also based on information theory (pretest entropy minus posttest entropy) has been criticized as failing, in some cases, to agree with our intuitive concept of diagnostic in...
In diagnostic decision-support systems, test selection amounts to selecting, in a sequential manner,...
This paper is a review of a particular approach to the method of maximum entropy as a general framew...
l H(x): Entropy- a measure of the information contained of a random variable- For Bernoulli random v...
Information theory has gained application in a wide range of disciplines, including statistical inf...
The use of gold standard procedures in screening may be costly, risky or even unethical. It is, ther...
In medical emergency situations, the triage process allows patients in potentially life-threatening ...
Paper presented at the 4th Strathmore International Mathematics Conference (SIMC 2017), 19 - 23 June...
Searching for information is critical in many situations. In medicine, for instance, careful choice ...
this paper we measure fidelity using relative entropy because, in the asymmetric communication examp...
Shannon's famous paper [1] paved the way to a theory called information theory. In essence, the...
Background: Entropy belongs to the few basic measurable entities in nature. It measures the distance...
We review a decision theoretic, i.e., utility-based, motivation for entropy and Kullback-Leibler rel...
In decision-making systems, how to measure uncertain information remains an open issue, especially f...
Various modifications have been suggested in the past to extend the Shannon entropy to continuous ra...
Nonlinear techniques have found an increasing interest in the dynamical analysis of various kinds of...
In diagnostic decision-support systems, test selection amounts to selecting, in a sequential manner,...
This paper is a review of a particular approach to the method of maximum entropy as a general framew...
l H(x): Entropy- a measure of the information contained of a random variable- For Bernoulli random v...
Information theory has gained application in a wide range of disciplines, including statistical inf...
The use of gold standard procedures in screening may be costly, risky or even unethical. It is, ther...
In medical emergency situations, the triage process allows patients in potentially life-threatening ...
Paper presented at the 4th Strathmore International Mathematics Conference (SIMC 2017), 19 - 23 June...
Searching for information is critical in many situations. In medicine, for instance, careful choice ...
this paper we measure fidelity using relative entropy because, in the asymmetric communication examp...
Shannon's famous paper [1] paved the way to a theory called information theory. In essence, the...
Background: Entropy belongs to the few basic measurable entities in nature. It measures the distance...
We review a decision theoretic, i.e., utility-based, motivation for entropy and Kullback-Leibler rel...
In decision-making systems, how to measure uncertain information remains an open issue, especially f...
Various modifications have been suggested in the past to extend the Shannon entropy to continuous ra...
Nonlinear techniques have found an increasing interest in the dynamical analysis of various kinds of...
In diagnostic decision-support systems, test selection amounts to selecting, in a sequential manner,...
This paper is a review of a particular approach to the method of maximum entropy as a general framew...
l H(x): Entropy- a measure of the information contained of a random variable- For Bernoulli random v...