Results 121 to 130 of about 100,889 (161)

Circular Inference in Dementia Diagnostics

Journal of Alzheimer's Disease, 2018
Referring to recent international articles stating that amyloid imaging or detection has a high additive value in making a diagnosis of Alzheimer’s disease (AD) when previous investigations are inconclusive, the authors of this editorial argue that this statement is based on circular reasoning and, hence, misleading.
Høilund-Carlsen, Poul F., Barrio, Jorge R., Gjedde, Albert, Werner, Thomas J., Alavi, Abass   +4 more
openaire   +5 more sources

Diagnostic plots for improved parameterization in Bayesian inference

Biometrika, 1993
SUMMARY A major problem with the Bayesian analysis of statistical models is that the computation of posterior and predictive summaries typically requires the numerical evaluation of complicated multivariate integrals. The accuracy and efficiency of these computations are usually sensitive to the choice of parameterization for the statistical model ...
Hills, Susan E., Smith, Adrian F. M.
openaire   +1 more source

Abduction and Diagnostic Inference

1990
Abduction is a type of logic or reasoning which derives plausible explanations for the data at hand. In this book, formal and computational models of the abductive reasoning process that underlies diagnostic problem- solving are considered. The core material presented is that of “parsimonious covering theory” and various extensions to it.
Yun Peng, James A. Reggia
openaire   +1 more source

Guidelines for using diagnostic imaging devices: an inference system

International Journal of Medical Informatics, 1999
This paper deals with optimising the use of magnetic resonance imaging (MRI) scanners through the development of a new kind of clinical guidelines called 'substrate-specific protocols'. These protocols would link the descriptive elements of lesions to the most appropriate imaging techniques on the basis of the biophysics of MRI.
Reuzel, R.P.B., Vries Robbé, P.F. de
openaire   +3 more sources

Nonparametric Predictive Inference for Accuracy of Ordinal Diagnostic Tests

Journal of Statistical Theory and Practice, 2012
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Frank Coolen
exaly   +3 more sources

Profile-Likelihood Inference for Highly Accurate Diagnostic Tests

Biometrics, 2002
We consider profile-likelihood inference based on the multinomial distribution for assessing the accuracy of a diagnostic test. The methods apply to ordinal rating data when accuracy is assessed using the area under the receiver operating characteristic (ROC) curve.
Tsimikas, John V., Bosch, Ronald J., Coull, Brent A., El Barmi, Hammou   +3 more
openaire   +3 more sources

Robust Diagnostics for Rank-Based Inference

1988
Abstract : Diagnostics based on robust R-estimates of regression coefficients are developed. These methods are not as sensitive to influential points as least squares diagnostics. In data sets with several influential points, diagnostics based on a robust fit have a greater chance of detecting interesting cases for further inspection.
Thomas P. Hettmansperger, Simon J. Sheather, Joseph W. McKean   +2 more
openaire   +1 more source

A Comment on Diagnostic Tools for Counterfactual Inference

Political Analysis, 2009
We evaluate two diagnostic tools used to determine if counterfactual analysis requires extrapolation. Counterfactuals based on extrapolation are model dependent and might not support empirically valid inferences. The diagnostics help researchers identify those counterfactual “what if” questions that are empirically plausible.
Nicholas Sambanis, Alexander Michaelides
openaire   +1 more source

Causal and diagnostic inferences: A comparison of validity

Organizational Behavior and Human Performance, 1981
Abstract Decision-support technologies are founded on the paradigm that direct judgments are less reliable and less valid than synthetic inferences produced from more “fragmentary” judgments. Moreover, certain types of fragments are normally assumed to be more valid than others.
Michael Burns, Judea Pearl
openaire   +1 more source

A factor graph inference algorithm for diagnostic Bayesian networks

2011 Seventh International Conference on Natural Computation, 2011
Factor tree inference algorithm (FTI) is an exact inference algorithm for diagnostic Bayesian networks (DBNs). Through computation sharing, the efficiency of FTI can be superior to conventional exact inference algorithms when answering multiple queries.
Yungang Zhu, Dayou Liu
exaly   +2 more sources