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PubMedDate not supplied

[The use of biochemical blood indices for the laboratory diagnosis of internal diseases using the automated complex device-computer].

Application of biochemical parameters of blood, reflecting disturbances in lipid, protein, carbohydrate, pigment and water-saline metabolism for diagnostics for internal organs diseases is discussed. Methods of clinical biochemistry in combination with subsequent automatic processing of the data obtained on the basis of probability theory and mathematical statistics methods can be used for preliminary computer diagnosis and further examination of a patient, as well as for construction of specific complexes of symptoms for some diseases. Due to their mobility, the preliminary computer diagnostics data can be successfully applied to different pathologies and groups of population.

Blood Chemical Analysis↗
PubMed1966

Selection of students for admission to medical school: A two-class decision approach.

The validity coefficient alone does not communicate sufficient information to estimate the errors in decisions to accept or reject candidates. By means of probability theory, it is demonstrated how information concerning errors in decisions may be estimated. With estimates of the frequencies of correct and incorrect decisions and the costs of such decisions, a utility index was defined, for which a minimum was sought as a function of the entrance requirement. Under the analytic criterion defined for utility, it was possible to determine for a number of cost systems the entrance score which would, in the long run, reduce losses to a minimum. The application of the model is illustrated using empirical data and hypothetical cost systems. For these data entrance requirements were determined according to the criterion in addition to selection ratios and probabilities of success.

Aptitude Tests↗
PubMed2000

Familiarity Bias and Belief Reversal in Relative Likelihood Judgment.

People are often called on to make an assessment of the relative likelihood of events (e.g., which of two investments is more likely to outperform the market?) and their complements (which of the two investments is more likely to perform no better than the market?). Probability theory assumes that belief orderings over events and their complements should mirror each other (i.e., P(A) >/= P(B) iff P (not-A) </= P(not-B)). This principle is violated in several surveys in which we asked people to assess the relative likelihood of familiar versus unfamiliar events. In particular, respondents are biased to view more familiar events (and their complements) as more likely than less familiar events (and their complements). Similarly, we observe that subjects are biased to view less familiar events (and their complements) as less likely than more familiar events (and their complements). Further studies demonstrate that the familiarity bias is less pronounced among subjects who are asked to judge the probability of each event rather than which event is more likely. Moreover, a greater proportion of subjects rate the more familiar event as more likely than assign a higher probability to that event. These patterns can be construed as belief reversals, analogous to the preference reversal phenomenon in decision making. The data are consistent with a contingent weighting model in which the process of judging relative likelihood biases attention toward evidence supporting the target hypothesis (and away from evidence supporting its complement). Because it is easier to recruit evidence supporting familiar events than unfamiliar events, this skewed attention causes both familiar events and their complements to be judged more likely, on average, than unfamiliar events and their complements. Copyright 2000 Academic Press.

Journal Article↗
PubMed2003

Multisampling suprathreshold perimetry: a comparison with conventional suprathreshold and full-threshold strategies by computer simulation.

PURPOSE: To compare a multisampling suprathreshold strategy with conventional suprathreshold and full-threshold strategies in detecting localized visual field defects and in quantifying the area of loss. METHODS: Probability theory was applied to examine various suprathreshold pass criteria (i.e., the number of stimuli that have to be seen for a test location to be classified as normal). A suprathreshold strategy that requires three seen or three missed stimuli per test location (multisampling suprathreshold) was selected for further investigation. Simulation was used to determine how the multisampling suprathreshold, conventional suprathreshold, and full-threshold strategies detect localized field loss. To determine the systematic error and variability in estimates of loss area, artificial fields were generated with clustered defects (0-25 field locations with 8- and 16-dB loss) and, for each condition, the number of test locations classified as defective (suprathreshold strategies) and with pattern deviation probability less than 5% (full-threshold strategy), was derived from 1000 simulated test results. RESULTS: The full-threshold and multisampling suprathreshold strategies had similar sensitivity to field loss. Both detected defects earlier than the conventional suprathreshold strategy. The pattern deviation probability analyses of full-threshold results underestimated the area of field loss. The conventional suprathreshold perimetry also underestimated the defect area. With multisampling suprathreshold perimetry, the estimates of defect area were less variable and exhibited lower systematic error. CONCLUSIONS: Multisampling suprathreshold paradigms may be a powerful alternative to other strategies of visual field testing. Clinical trials are needed to verify these findings.

Computer Simulation↗
PubMed2002

Validation of HPLC and GC-MS systems for bisphenol-A leached from hemodialyzers on the basis of FUMI theory.

This paper proposes a method for the validation of chromatography systems in which many experiments to estimate SD or RSD are difficult or impossible to carry out because of time, cost, etc. HPLC systems with UV-Vis and fluorescence detectors and GC-MS system for bisphenol-A leached from hemodialyzers are taken as an example. Examined as validation characteristics are not only the ordinary quantities (precision, accuracy, range, limit of detection (LOD), limit of quantitation (LOQ), specificity and linearity) but also precision plots (measurement RSD vs. concentration), 95% confidence intervals of calibration lines and LOD signals over baselines. The precision plots, calibration confidence intervals and LOD signals are shown to be advantageous to validate and compare the analytical performance of the systems. The LOD, LOQ, precision plots and 95% confidence intervals of calibration lines are all derived from the SD of measurements and the reliability of these quantities and plots depends totally on the reliability of the SD estimates. This paper uses a probability theory, called the FUMI theory, to estimate as exact a measurement SD as possible without the replication. The precision of the HPLC and GC-MS systems is shown to coincide with the repeatability obtained by the repetition of measurements.

Benzhydryl Compounds↗
PubMed1984

Coordination of neuronal signals as structures in state space.

This paper expresses difficulties we have in interpreting neuronal activities by means of information and probability theory: until now there is no general agreement about the alphabet used by the neurons and, consequently, the first step in information theory is actually a conjecture. Further, electrophysiological single unit records can often be shown to be not stationary (because of trends, facilitations, inhibitions, transient reactions or oscillations). Thus they would not appear to be ergodic. But then, how does the system succeed in recognizing certain patterns by only one realization of a stochastic process? These difficulties do not arise if an appropriate multiunit system is considered, the dynamics of which are determined by a set of differential equations. The asymptotic (t----infinity) solutions of these equations define a number of state space structures (fixed points, limit cycles or strange attractors). According to this concept, information is related to the special shape of a state space structure and its probability, and information flow means the filtering of these structures.

Animals↗
PubMedDate not supplied

Medical expert systems based on causal probabilistic networks.

Causal probabilistic networks (CPNs) offer new methods by which you can build medical expert systems that can handle all types of medical reasoning within a uniform conceptual framework. Based on the experience from a commercially available system and a couple of large prototype systems, it appears that CPNs are now an attractive alternative to other methods. A CPN is an intensional model of a domain, and it is therefore conceptually much closer to qualitative reasoning systems and to simulation systems than to rule-based or logic-based systems. Recent progress in Bayesian inference in networks has yielded computationally efficient methods. The inference method used follows the fundamental axioms of probability theory, and gives a sound framework for causal and diagnostic (deductive and abductive) reasoning under uncertainty. Experience with the prototypes indicates that it may be possible to use decision theory as a rational approach to test planning and therapy planning. The way in which knowledge is acquired and represented in CPNs makes it easy to express 'deep knowledge' for example in the form of physiological models, and the facilities for learning make it possible to make a smooth transition from expert opinion to statistics based on empirical data.

Artificial Intelligence↗
PubMed2000

Stochastic model of hysteresis

The methods of the probability theory have been used in order to build up a model of hysteresis which is different from the well-known Preisach model. It is assumed that the system consists of large number of abstract particles in which the variation of an external control parameter (e.g., the magnetic field) may result in transitions between two states S((+)) and S((-)). The state of a particle is characterized by the value +1 or -1 of a random variable (e.g., the magnetization direction parallel or antiparallel to the magnetic field). The transitions are governed by two further random variables corresponding to the S((-))-->S((+)) and the S((+))-->S((-)) transitions (e.g., "up switching" and "down switching magnetic field"). The method presented here makes it possible to calculate the probability distribution and consequently the expectation value of the number of particles in the S((+)) (or S((-))) state for both increasing and decreasing parameter values, i. e., the hysteresis curves of the transitions can be determined. It turns out that the reversal points of the control parameter are Markov points which determine the stochastic evolution of the process. It has been shown that the branches of the hysteresis loop are converging to fixed limit curves when the number of cyclic back-and-forth variations of the control parameter between two consecutive reversal points is large enough. This convergence to limit curves gives a clear explanation of the accommodation process. The accommodated minor loops show the return-point memory property but this property is obviously absent in the case of nonaccommodated minor loops which are not congruent and generally not closed. In contrast to the traditional Preisach model the reversal point susceptibilities are nonzero finite values. The stochastic model can provide a surprisingly good approximation of the Raylaigh quadratic law when the external parameter varies between two sufficiently small values. The practical benefits of the model can be seen in the numerical analysis of the derived equations. On one hand the calculated curves are in good qualitative agreement with the experimental observations and on the other hand, the estimation of the joint distribution function of the up and down switching fields can be performed by using the measured hysteresis curves.

Journal Article↗
PubMed2005

Incorporating a hydrophobic solid into a coarse grain liquid framework: graphite in an aqueous amphiphilic environment.

A method is presented for incorporating a solid into a coarse grain liquid model. From the fully atomistic solid-liquid site-site description the solid is replaced by an implicit potential. The liquid particles are then coarse grained by appealing to statistical mechanics and probability theory. The dimensionality problem which arises is overcome with an approximate treatment and a force field is derived for graphite interacting with an existing coarse grain liquid model. Water is considered separately by using the experimentally observed contact angle between a water droplet and a graphite surface. Finally, the solid is restored to an explicit representation to allow for different geometries.

Adsorption↗
PubMed1980

Glomerular epithelial foot processes in normal man and rats. Distribution of true width and its intra- and inter-individual variation.

The width of individual glomerular epithelial foot processes appears very different on electron micrographs. A method for obtainining distributions of the true width of foot processes from that of their apparent width on electron micrographs has been developed based on geometric probability theory pertaining to a specific geometric model. Analyses of foot process width in humans and rats show a remarkable interindividual invariance implying rigid control and therefore great biological significance of foot process width or a derivative thereof. The very low inter-individual variation of the true width, shown in the present paper, makes it possible to demonstrate slight changes in rather small groups of patients or experimental animals.

Adolescent↗
PubMed2003

Evaluation of decay times in coupled spaces: Bayesian decay model selection.

This paper applies Bayesian probability theory to determination of the decay times in coupled spaces. A previous paper [N. Xiang and P. M. Goggans, J. Acoust. Soc. Am. 110, 1415-1424 (2001)] discussed determination of the decay times in coupled spaces from Schroeder's decay functions using Bayesian parameter estimation. To this end, the previous paper described the extension of an existing decay model [N. Xiang, I. Acoust. Soc. Am. 98, 2112-2121 (1995)] to incorporate one or more decay modes for use with Bayesian inference. Bayesian decay time estimation will obtain reasonable results only when it employs an appropriate decay model with the correct number of decay modes. However, in architectural acoustics practice, the number of decay modes may not be known when evaluating Schroeder's decay functions. The present paper continues the endeavor of the previous paper to apply Bayesian probability inference for comparison and selection of an appropriate decay model based upon measured data. Following a summary of Bayesian model comparison and selection, it discusses selection of a decay model in terms of experimentally measured Schroeder's decay functions. The present paper, along with the Bayesian decay time estimation described previously, suggests that Bayesian probability inference presents a suitable approach to the evaluation of decay times in coupled spaces.

Journal Article↗
PubMed2003

Covariances among join-count spatial autocorrelation measures.

Spatial distributions of biological variables are often well-characterized with pairwise measures of spatial autocorrelation. In this article, the probability theory for products and covariances of join-count spatial autocorrelation measures are developed for spatial distributions of multiple nominal (e.g. species or genotypes) types. This more fully describes the joint distributions of pairwise measures in spatial distributions of multiple (i.e. more than two) types. An example is given on how the covariances can be used for finding standard errors of weighted averages of join-counts in spatial autocorrelation analysis of more than two types, as is typical for genetic data for multiallelic loci.

Analysis of Variance↗
PubMed1996

A statistical approach for analyzing clonogenic survival data.

The assay of colony-forming efficiency is a mainstay in the measurement of cell response in vitro to many physical and chemical agents. Currently, data on colony-forming efficiency can be calculated in a variety of ways. Authors rarely describe in detail the methods used to determine the extent of biological variation within experiments. The use of standard methods of data analysis and presentation would improve interpretation of data and facilitate comparison between laboratories. Here we propose such a method. Binomial and Poisson probability theory were used to increase the accuracy of the estimate of the surviving fraction and to create an objective criterion for determining whether data obtained from serial dilutions of cell numbers used in the assay of colony-forming efficiency should be excluded or included for further analysis. The variability inherent in the calculation of surviving fraction was determined by using Fieller's theorem, a special statistical application for assessing ratios of estimates, to determine the 95% confidence interval. All calculations were done on a simple and commercially available spreadsheet program.

Cell Line↗
PubMed1990

An investigation of test-house variability in the mechanical testing of dental materials and the statistical treatment of results.

The suitability of a test for standard specification testing depends inter alia on the ability to repeat the tests in a reproducible manner at a number of test centres. This work involved the investigation of three tests currently proposed as standard specification tests for dental materials. It was found that one test (compressive strength of cements) is inappropriate for inclusion in standards due to an unacceptable variation in test results between test centres. The treatment of results suggested in standards should place less emphasis on the mean value of a relatively small number of test specimens and the use of a simple form of probability theory in which, say, 80 per cent of specimens are required to achieve a certain pass level. In some standards there may be a need to increase the numbers of test specimens significantly in order to achieve a more meaningful and reliable result. The use of Weibull statistics can be adopted as a means of identifying tests which are suitable for inclusion in standard specifications, although it is doubtful that a test at this level of sophistication is required or desirable for inclusion in the standards themselves.

Composite Resins↗
PubMed1995

Theory and application of the maximum likelihood principle to NMR parameter estimation of multidimensional NMR data.

A general theory has been developed for the application of the maximum likelihood (ML) principle to the estimation of NMR parameters (frequency and amplitudes) from multidimensional time-domain NMR data. A computer program (ChiFit) has been written that carries out ML parameter estimation in the D-1 indirectly detected dimensions of a D-dimensional NMR data set. The performance of this algorithm has been tested with experimental three-dimensional (HNCO) and four-dimensional (HN(CO)-CAHA) data from a small protein labeled with 13C and 15N. These data sets, with different levels of digital resolution, were processed using ChiFit for ML analysis and employing conventional Fourier transform methods with prior extrapolation of the time-domain dimensions by linear prediction. Comparison of the results indicates that the ML approach provides superior frequency resolution compared to conventional methods, particularly under conditions of limited digital resolution in the time-domain input data, as is characteristic of D-dimensional NMR data of biomolecules. Close correspondence is demonstrated between the results of analyzing multidimensional time-domain NMR data by Fourier transformation, Bayesian probability theory [Chylla, R.A. and Markley, J.L. (1993) J. Biomol. NMR, 3, 515-533], and the ML principle.

Algorithms↗
PubMed1990

Covariance in parasite burdens: the effect of predisposition to infection.

Recently the phenomenon of predisposition to helminth infection has been reported in a number of studies: those individuals which are heavily infected before treatment with an anthelmintic tend also to acquire heavy parasite burdens following a period of reinfection. This correlation between parasite burdens in initial and reinfections is generated by differences between hosts in their exposure to infective stages and in their susceptibility to infection. Inter-host differences in these factors also generate the aggregated or over-dispersed parasite distributions that are usually observed. This paper uses probability theory to predict the correlation between initial and reinfection parasite burdens assuming that those inter-host differences which generate over-dispersion remain constant for a given individual between initial and reinfection periods. The predicted correlation is considerably greater than is observed in most published data sets. Over-dispersion is thus generated by variability between hosts which has components that remain constant between initial and reinfection and also components which vary between infection periods. The model is modified to account for those two sources of variability, and the result applied to published data to determine the contributions made by short and long-term factors to the observed distributions.

Analysis of Variance↗
PubMedDate not supplied

[Exposure levels of persons involved in cleaning-up after the Chernobyl AES accident and included in the Russian State Medical and Dosimetric Registry].

Theoretical and practical problems related to the dosimetric data verification for recovery workers at the Chernobyl NBB are considered. Approaches and conclusions presented in the paper of L.A. Ilyin at al, (1). By using probability theory it was clearly that the method of dose verification developed in the reviewed paper and based on delta-entropy of statistical distribution failed to be scientifically founded. It does not permit to prove the existence of non-random component in random sampling without additional assumptions. The main conclusion of the reviewed paper, that 60% of individual doses included in the all-russia state medical and dosimetric state registry (ARMDSR) differ from the real exposure doses, is analysed and quantitatively estimated for several group of recovery workers. Our results present evidence that ARMDSR data do not contain a considerable part of "distorted" values even if the above mentioned method to take as valid.

Humans↗
PubMed2004

An experimental method for measuring the mean length of cerebellar parallel fibers: validation and derivation of a correction factor by computational simulation and probability analysis.

The length of cerebellar parallel fibers is important for information integration by the Purkinje cells. Based on the Copernican principle for analyzing the length of stochastic events, we have recently devised a stochastic method to estimate the mean length of parallel fibers within a given cerebellar region. The purpose of the present report is to provide validation of this methodology via computational simulations. We create virtual parallel fibers with known lengths and program each step of our stochastic method for computational simulation. We then compare the observed mean length obtained from our computational simulation with the known mean length of the virtual parallel fibers. In particular, we investigate the effect of cutting parallel fibers into segments during histological sectioning. Our computational results reveal an over-estimation factor ranging from 1.0 (no correction is necessary) to 2.0 as the parallel fiber segmentation becomes increasingly severe. Based on probability theory considerations, we have confirmed the existence of this over-estimation. We have further determined the cause of this over-estimation to be an artificial consequence of one of the sampling steps in our stochastic method. These results provide validation of our methodology, as well as a correction factor, which can be derived directly from the experimentally measured parameters and used to obtain the true mean length of parallel fibers. Potential applications of the stochastic method include a comparative analysis of the length of parallel fibers as an approach to gain clues about cerebellar circuit principles and function. In addition, the stochastic method may also find promising applications in other functionally important axonal systems in the brain.

Cerebellar Cortex↗