997 resultados para GLAUCOMA PROBABILITY SCORE


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Score following has been an important area of research in AI and music since the mid 80's. Various systems were developed, but they were predominantly for providing automated accompaniment to live concert performances, dealing mostly with issues relating to pitch detection and identification of embellished melodies. They have a big potential in the area of education where student performers benefit in practice situations. Current accompaniment systems are not designed to deal with errors that may occur during practising. In this paper we present a system developed to provide accompaniment for students practising at home. First a survey of score following will be given. Then the capabilities of the system will be explained, and the results from the first experiments of the monophonic score following system will be presented.

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The chain growth probability (alpha value) is one of the most significant parameters in Fischer-Tropsch (FT) synthesis. To gain insight into the chain growth probability, we systematically studied the hydrogenation and C-C coupling reactions with different chain lengths on the stepped Co(0001) surface using density functional theory calculations. Our findings elucidate the relationship between the barriers of these elementary reactions and the chain length. Moreover, we derived a general expression of the chain growth probability and investigated the behavior of the alpha value observed experimentally. The high methane yield results from the lower chain growth rate for C-1 + C-1 coupling compared with the other coupling reactions. After C-1, the deviation of product distribution in FT synthesis from the Anderson-Schulz-Flory distribution is due to the chain length-dependent paraffin/olefin ratio. (C) 2008 Elsevier Inc. All rights reserved.

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The standard linear-quadratic (LQ) survival model for external beam radiotherapy is reviewed with particular emphasis on studying how different schedules of radiation treatment planning may be affected by different tumour repopulation kinetics. The LQ model is further examined in the context of tumour control probability (TCP) models. The application of the Zaider and Minerbo non-Poissonian TCP model incorporating the effect of cellular repopulation is reviewed. In particular the recent development of a cell cycle model within the original Zaider and Minerbo TCP formalism is highlighted. Application of this TCP cell-cycle model in clinical treatment plans is explored and analysed.

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BACKGROUND: Cardiovascular disease (CVD) occurs more frequently in individuals with a family history of premature CVD. Within families the demographics of CVD are poorly described. DESIGN: We examined the risk estimation based on the Systematic Coronary Risk Evaluation (SCORE) system and the Joint British Guidelines (JBG) for older unaffected siblings of patients with premature CVD (onset ≤55 years for men and ≤60 years for women). METHODS: Between August 1999 and November 2003 laboratory and demographic details were collected on probands with early-onset CVD and their older unaffected siblings. Siblings were screened for clinically overt CVD by a standard questionnaire and 12-lead electrocardiogram (ECG). RESULTS: A total of 790 siblings was identified and full demographic details were available for 645. The following siblings were excluded: 41 with known diabetes mellitus; seven with random plasma glucose of 11.1 mmol/l or greater; and eight with ischaemic ECG. Data were analysed for 589 siblings from 405 families. The mean age was 55.0 years, 43.1% were men and 28.7% were smokers. The mean total serum cholesterol was 5.8 mmol/l and hypertension was present in 49.4%. Using the SCORE system, when projected to age 60 years, 181 men (71.3%) and 67 women (20.0%) would be eligible for risk factor modification. Using JBG with a 10-year risk of 20% or greater, 42 men (16.5%) and four women (1.2%) would be targeted. CONCLUSIONS: Large numbers of these asymptomatic individuals meet both European and British guidelines for the primary prevention of CVD and should be targeted for risk factor modification. The prevalence of individuals defined as eligible for treatment is much higher when using the SCORE system. © 2007 European Society of Cardiology.

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Logistic regression and Gaussian mixture model (GMM) classifiers have been trained to estimate the probability of acute myocardial infarction (AMI) in patients based upon the concentrations of a panel of cardiac markers. The panel consists of two new markers, fatty acid binding protein (FABP) and glycogen phosphorylase BB (GPBB), in addition to the traditional cardiac troponin I (cTnI), creatine kinase MB (CKMB) and myoglobin. The effect of using principal component analysis (PCA) and Fisher discriminant analysis (FDA) to preprocess the marker concentrations was also investigated. The need for classifiers to give an accurate estimate of the probability of AMI is argued and three categories of performance measure are described, namely discriminatory ability, sharpness, and reliability. Numerical performance measures for each category are given and applied. The optimum classifier, based solely upon the samples take on admission, was the logistic regression classifier using FDA preprocessing. This gave an accuracy of 0.85 (95% confidence interval: 0.78-0.91) and a normalised Brier score of 0.89. When samples at both admission and a further time, 1-6 h later, were included, the performance increased significantly, showing that logistic regression classifiers can indeed use the information from the five cardiac markers to accurately and reliably estimate the probability AMI. © Springer-Verlag London Limited 2008.

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The sediment sequence from Hasseldala port in southeastern Sweden provides a unique Lateglacial/early Holocene record that contains five different tephra layers. Three of these have been geochemically identified as the Borrobol Tephra, the Hasseldalen Tephra and the 10-ka Askja Tephra. Twenty-eight high-resolution C-14 measurements have been obtained and three different age models based on Bayesian statistics are employed to provide age estimates for the five different tephra layers. The chrono- and pollen stratigraphic framework supports the stratigraphic position of the Borrobol Tephra as found in Sweden at the very end of the Older Dryas pollen zone and provides the first age estimates for the Askja and Hasseldalen tephras. Our results, however, highlight the limitations that arise in attempting to establish a robust, chronologically independent lacustrine sequence that can be correlated in great detail to ice core or marine records. Radiocarbon samples are prone to error and sedimentation rates in lake basins may vary considerably due to a number of factors. Any type of valid and 'realistic' age model, therefore, has to take these limitations into account and needs to include this information in its prior assumptions. As a result, the age ranges for the specific horizons at Hasseldala port are large and calendar year estimates differ according to the assumptions of the age-model. Not only do these results provide a cautionary note for overdependence on one age-model for the derivation of age estimates for specific horizons, but they also demonstrate that precise correlations to other palaeoarchives to detect leads or lags is problematic. Given the uncertainties associated with establishing age-depth models for sedimentary sequences spanning the Lateglacial period, however, this exercise employing Bayesian probability methods represents the best possible approach and provides the most statistically significant age estimates for the pollen zone boundaries and tephra horizons. Copyright (C) 2006 John Wiley & Sons, Ltd.

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In this article, we extend the earlier work of Freeland and McCabe [Journal of time Series Analysis (2004) Vol. 25, pp. 701–722] and develop a general framework for maximum likelihood (ML) analysis of higher-order integer-valued autoregressive processes. Our exposition includes the case where the innovation sequence has a Poisson distribution and the thinning is binomial. A recursive representation of the transition probability of the model is proposed. Based on this transition probability, we derive expressions for the score function and the Fisher information matrix, which form the basis for ML estimation and inference. Similar to the results in Freeland and McCabe (2004), we show that the score function and the Fisher information matrix can be neatly represented as conditional expectations. Using the INAR(2) speci?cation with binomial thinning and Poisson innovations, we examine both the asymptotic e?ciency and ?nite sample properties of the ML estimator in relation to the widely used conditional least
squares (CLS) and Yule–Walker (YW) estimators. We conclude that, if the Poisson assumption can be justi?ed, there are substantial gains to be had from using ML especially when the thinning parameters are large.

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It is shown that, when expressing arguments in terms of their logarithms, the Laplace transform of a function is related to the antiderivative of this function by a simple convolution. This allows efficient numerical computations of moment generating functions of positive random variables and their inversion. The application of the method is straightforward, apart from the necessity to implement it using high-precision arithmetics. In numerical examples the approach is demonstrated to be particularly useful for distributions with heavy tails, Such as lognormal, Weibull, or Pareto distributions, which are otherwise difficult to handle. The computational efficiency compared to other methods is demonstrated for an M/G/1 queueing problem.

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The development of methods providing reliable estimates of demographic parameters (e. g., survival rates, fecundity) for wild populations is essential to better understand the ecology and conservation requirements of individual species. A number of methods exist for estimating the demographics of stage-structured populations, but inherent mathematical complexity often limits their uptake by conservation practitioners. Estimating survival rates for pond-breeding amphibians is further complicated by their complex migratory and reproductive behaviours, often resulting in nonobservable states and successive cohorts of eggs and tadpoles. Here we used comprehensive data on 11 distinct breeding toad populations (Bufo calamita) to clarify and assess the suitability of a relatively simple method [the Kiritani-Nakasuji-Manly (KNM) method] to estimate the survival rates of stage-structured populations with overlapping life stages. The study shows that the KNM method is robust and provides realistic estimates of amphibian egg and larval survival rates for species in which breeding can occur as a single pulse or over a period of several weeks. The study also provides estimates of fecundity for seven distinct toad populations and indicates that it is essential to use reliable estimates of fecundity to limit the risk of under- or overestimating the survival rates when using the KNM method. Survival and fecundity rates for B. calamita populations were then used to define population matrices and make a limited exploration of their growth and viability. The findings of the study recently led to the implementation of practical conservation measures at the sites where populations were most vulnerable to extinction. © 2010 The Society of Population Ecology and Springer.