Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “Probability Theory”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2Linked to original sources
PubMed1986

Probability theory in the use of diagnostic tests. An introduction to critical study of the literature.

The purpose of this article is to provide an understanding of methods that are useful in formulating advice about when to use diagnostic tests. If the clinician expresses diagnostic uncertainty as the probability of a disease in a patient, Bayes' theorem may be used to predict the effect of doing various tests and their impact on patient management. To use Bayes' theorem wisely, one must be aware of pitfalls in estimating probability and must understand the limitations of most studies of the sensitivity and specificity of diagnostic tests.

Bayes Theorem↗
PubMed1997

[Evaluation of the risk of decompression disease during hypobaric decompression from the standpoint of the probability theory].

Author's probabilistic theory of decompression sickness (DS) asserts that DS risk for human subjects during a single-stage reduction of pressure will be rated by distribution of estimated nucleation efficiency in the "worst" body tissues and its critical value as a function of initial nitrogen pressure, end-pressure, and bubble growth dynamics. The method was tested in the analysis of literature on the DS risk during altitude exposures with preliminary denitrogenation of varying length. Results of the analysis suggest that washing out half of nitrogen from the "worst" tissues will take minimum 480 minutes instead of 360 minutes. Calculated parameters of nucleation in tissues were used to plot DS risk due to hypobaric decompression against the final pressure. Influence of physical activity on nucleation parameters and DS risk curves is discussed.

Decompression↗
PubMed1998

[Analysis of decompression safety during extravehicular activity of astronauts in the light of probability theory].

Objectives of the study were comparative assessment of the risk of decompression sickness (DCS) in human subjects during shirt-sleeve simulation of extravehicular activity (EVA) following Russian and U.S. protocols, and analysis of causes of the difference between real and simulated EVA decompression safety. To this end, DCS risk during exposure to a sing-step decompression was estimated with an original method. According to the method, DCS incidence is determined by distribution of nucleation efficacy index (z) in the worst body tissues and its critical values (zm) as a function of initial nitrogen tension in these tissues and final ambient pressure post decompression. Gaussian distribution of z values was calculated basing on results of the DCS risk evaluation on the U.S. EVA protocol in an unsuited chamber test with various pre-breath procedures (Conkin et al., 1987). Half-time of nitrogen washout from the worst tissues was presumed to be 480 min. Calculated DCS risk during short-sleeve EVA simulation by the Russian and U.S. protocols with identical physical loading made up 19.2% and 23.4%, respectively. Effects of the working spacesuit pressure, spacesuit rigidity, metabolic rates during operations in EVA space suit, transcutaneous nitrogen exchange in the oxygen atmosphere of space suit, microgravity, analgesics, short compression due to spacesuit leak tests on the eye of EVA are discussed. Data of the study illustrate and advocate for high decompression safety of current Russian and U.S. EVA protocols.

Astronauts↗
PubMed2006

Modeling water diffusion anisotropy within fixed newborn primate brain using Bayesian probability theory.

An active area of research involves optimally modeling brain diffusion MRI data for various applications. In this study Bayesian analysis procedures were used to evaluate three models applied to phase-sensitive diffusion MRI data obtained from formalin-fixed perinatal primate brain tissue: conventional diffusion tensor imaging (DTI), a cumulant expansion, and a family of modified DTI expressions. In the latter two cases the optimum expression was selected from the model family for each voxel in the image. The ability of each model to represent the data was evaluated by comparing the magnitude of the residuals to the thermal noise. Consistent with previous findings from other laboratories, the DTI model poorly represented the experimental data. In contrast, the cumulant expansion and modified DTI expressions were both capable of modeling the data to within the noise using six to eight adjustable parameters per voxel. In these cases the model selection results provided a valuable form of image contrast. The successful modeling procedures differ from the conventional DTI model in that they allow the MRI signal to decay to a positive offset. Intuitively, the positive offset can be thought of as spins that are sufficiently restricted to appear immobile over the sampled range of b-values.

Animals↗
PubMedDate not supplied

The feasibility of axiomatically-based expert systems.

We distinguish axiomatically-based expert systems, whose design and implementation are guided by one or more axiomatically-based theories of decision-making (e.g., decision theory, Bayesian probability theory, maximum entropy theory), from traditional expert systems. An analysis of the knowledge acquisition and computational needs of axiomatically-based expert systems is presented. An explicit quantitative comparison is made between the actual knowledge acquisition effort required to build an existing expert system, and the effort that would be required to build an analogous axiomatically-based advice system. The costs and benefits of the axiomatic approach are discussed. The analysis suggests that the small additional cost of knowledge acquisition for the axiomatic approach are outweighed by the long-term benefits this approach provides.

Computer Simulation↗
PubMed2002

[Axiomatic probability by the poet Abu Ala Al MA'ARRI].

The Arabic poet-philosopher Abu AJa AI Ma'ARRI says a famous verse announcing ten centuries before an axiom of the probability theory: that the probability of fundamental space is equal one; and only the death can prove this equality and all of unpredictable phenomenon of life base a probability lower than one.

Arab World↗