Results 241 to 250 of about 864,632 (271)
Some of the next articles are maybe not open access.
Applying Bayesian reasoning to electrocardiogram interpretation
Journal of Electrocardiology, 2023Electrocardiograms (ECGs) are a cornerstone in cardiac care. Traditional statistical metrics like sensitivity and specificity are commonly used for diagnostic evaluations but are limited when applied in clinical settings due to their inability to incorporate pre-test likelihoods or individual patient context.
openaire +2 more sources
The Scope of Bayesian Reasoning
PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association, 1992The Bayesian view of inference has become popular in philosophy in recent years. Scientific Reasoning: a Bayesian Approach, by Colin Howson and Peter Urbach, represents an articulate and persuasive defense of the Bayesian view. We focus on the theme of that book, and argue that there are difficulties with Bayesianism, and alternatives worth considering.
openaire +1 more source
A bayesian framework for case-based reasoning
1996In this paper we present a probabilistic framework for case-based reasoning in data-intensive domains, where only weak prior knowledge is available. In such a probabilistic viewpoint the attributes are interpreted as random variables, and the case base is used to approximate the underlying joint probability distribution of the attributes.
Henry Tirri +2 more
openaire +2 more sources
Eliciting an overlooked aspect of Bayesian reasoning
ACM SIGCSE Bulletin, 2007Bayesian theorem is the theoretical basis of uncertainty management as well as the stochastic foundation for forecast-oriented expert systems. Mathematically, the reasoning steps can be represented by a sequence of probabilistic computations.
openaire +2 more sources
On having no reason: dogmatism and Bayesian confirmation
Synthese, 2009Recently in epistemology a number of authors have mounted Bayesian objections to dogmatism. These objections depend on a Bayesian principle of evidential confirmation: Evidence E confirms hypothesis H just in case Pr(H|E) > Pr(H). I argue using Keynes’ and Knight’s distinction between risk and uncertainty that the Bayesian principle fails to ...
openaire +2 more sources
Integrating Deep Learning and Bayesian Reasoning
2019Deep learning (DL) is an excellent function estimator which has amazing result on perception tasks such as visualization recognition and text recognition. But, its inner architecture acts as a black box, because the users cannot understand why such decisions are made.
Sin Yin Tan +2 more
openaire +3 more sources
Essentials of Bayesian diagnostic reasoning
The Netherlands Journal of Medicine, 1995openaire +2 more sources