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Results for “probabilistic modelling”

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At least 1,117 records · Page 62Linked to original sources
PubMed2002

Development of an economic model to assess the cost effectiveness of asthma management strategies.

BACKGROUND AND OBJECTIVE: Asthma is a chronic-episodic disease characterised by acute, symptomatic episodes of varying severity. We developed a Markov model that can be used to estimate the cost effectiveness of alternative asthma treatments. Because of the costs they incur, asthma exacerbations ('attacks') requiring intervention by a healthcare professional were a central consideration in the development of the model. METHODS: Treatment success was assessed as asthma control, a composite measure based on goals defined in world-wide asthma management guidelines and in terms of quality-adjusted life-years (QALYs). The data from which the transition probabilities were derived came from patients with asthma who received either salmeterol/fluticasone propionate combination (SFC) 50/100microg or fluticasone propionate (FP) 100microg, administered twice daily via an inhaler, in a 12-week, randomised, double-blind, clinical trial. Costs were estimated from resource profiles defined for each of the model states. A key aspect of the model was the use of probabilistic sensitivity analysis techniques to examine the uncertainty in the cost-effectiveness results. Distributions were fitted to transition probabilities and to cost input parameters and values were sampled at random from these distributions using a second order Monte Carlo simulation technique. This produced a distribution for incremental cost effectiveness that was employed to construct 95% uncertainty intervals and to construct cost effectiveness acceptability curves. RESULTS: In this analysis, the model was run over a 12-week period using transition probabilities derived from the trial data. The results showed that treatment with SFC resulted in a higher proportion of successfully controlled weeks per patient than treatment with FP (66 vs 47%), and higher mean weekly direct asthma management costs (pound sterling 15.77 vs pound sterling 11.83; 2000 values). The average incremental cost per successfully controlled week with SFC was pound sterling 20.83. Probabilistic sensitivity analysis showed that the 95% uncertainty intervals for the incremental cost-effectiveness ratio was - pound sterling 64.94 to pound sterling 112.66. In approximately 25% of cases, SFC was dominant (more effective and less costly), but in the remaining cases, it was both more effective and more costly. It was shown that if decision makers are willing to pay approximately pound sterling 45 for an additional successfully controlled week, SFC will be the more cost-effective strategy in this patient population for 80% of the time. CONCLUSIONS: This is one of the first decision-analytic models of asthma to incorporate probabilistic sensitivity analysis techniques to explore uncertainty. The model's flexible yet standardised framework permits the cost effectiveness of alternative asthma management strategies in different healthcare settings to be established.

Adolescent↗
PubMed2006

Informing the efficient use of health care and health care research resources - the case of screening for abdominal aortic aneurysm in Sweden.

BACKGROUND: An analytical framework using Bayesian decision theory and value-of-information analysis has recently been advocated for the economic evaluation of health technologies. The purpose of this study was to apply this framework to screening for abdominal aortic aneurysm (AAA) in Sweden and to compare the conclusions from this study with the conclusions presented in an assessment performed by the Swedish Council of Technology Assessment (SBU). METHODS: A probabilistic decision-analytical model was developed to establish the cost-effectiveness of a screening programme for AAA relative to current clinical practice and to calculate the value-of-information. RESULTS: The cost per quality-adjusted life-year for screening was 9700 euro. The expected value of perfect information for the assessment of overall cost-effectiveness was low, suggesting little benefit in conducting further research. Expected value of perfect partial information indicated that rupture probabilities were associated with the highest uncertainty. By contrast, the SBU report concluded there was limited evidence of cost-effectiveness and proposed further research. CONCLUSION: The investigated screening programme for AAA is likely to be cost-effective and conducting another clinical trial is unlikely to add much valuable information to this decision problem. These recommendations contrast with the vaguer recommendations from SBU that more evidence is required of costs-effectiveness.

Aortic Aneurysm, Abdominal↗
PubMed2005

An automated approach to connectivity-based partitioning of brain structures.

We present an automated approach to the problem of connectivity-based partitioning of brain structures using diffusion imaging. White-matter fibres connect different areas of the brain, allowing them to interact with each other. Diffusion-tensor MRI measures the orientation of white-matter fibres in vivo, allowing us to perform connectivity-based partitioning non-invasively. Our new approach leverages atlas-based segmentation to automate anatomical labeling of the cortex. White-matter connectivities are inferred using a probabilistic tractography algorithm that models crossing pathways explicitly. The method is demonstrated with the partitioning of the corpus callosum of eight healthy subjects.

Algorithms↗
PubMed1993

Modeling vehicle accidents and highway geometric design relationships.

The statistical properties of four regression models--two conventional linear regression models and two Poisson regression models--are investigated in terms of their ability to model vehicle accidents and highway geometric design relationships. Potential limitations of these models pertaining to their underlying distributional assumptions, estimation procedures, functional form of accident rate, and sensitivity to short road sections, are identified. Important issues, such as the treatment of vehicle exposure and traffic conditions, and data uncertainties due to sampling and nonsampling errors, are also discussed. Roadway and truck accident data from the Highway Safety Information System (HSIS), a highway safety data base administered by the Federal Highway Administration (FHWA), have been employed to illustrate the use and the limitations of these models. It is demonstrated that the conventional linear regression models lack the distributional property to describe adequately random, discrete, nonnegative, and typically sporadic vehicle accident events on the road. As a result, these models are not appropriate to make probabilistic statements about vehicle accidents, and the test statistics derived from these models are questionable. The Poisson regression models, on the other hand, possess most of the desirable statistical properties in developing the relationships. However, if the vehicle accident data are found to be significantly overdispersed relative to its mean, then using the Poisson regression models may overstate or understate the likelihood of vehicle accidents on the road. More general probability distributions may have to be considered.

Accidents, Traffic↗
PubMedDate not supplied

Perceptual grouping and the interactions between visual cortical areas.

Visual perception involves the grouping of individual elements into coherent patterns, such as object representations, that reduce the descriptive complexity of a visual scene. The computational and physiological bases of this perceptual remain poorly understood. We discuss recent fMRI evidence from our laboratory where we measured activity in a higher object processing area (LOC), and in primary visual cortex (V1) in response to visual elements that were either grouped into objects or randomly arranged. We observed significant activity increases in the LOC and concurrent reductions of activity in V1 when elements formed coherent shapes, suggesting that activity in early visual areas is reduced as a result of grouping processes performed in higher areas. In light of these results we review related empirical findings of context-dependent changes in activity, recent neurophysiology research related to cortical feedback, and computational models that incorporate feedback operations. We suggest that feedback from high-level visual areas reduces activity in lower areas in order to simplify the description of a visual image-consistent with both predictive coding models of perception and probabilistic notions of 'explaining away.'

Animals↗
PubMed1998

Elongated physiological summation pools in the human visual cortex.

The visibility of gratings improves with increasing stimulus area. This effect is usually interpreted as being due to probability summation between the outputs of linear, independent spatial filters, although non-linear spatial summation can have similar effects [1]. In order to distinguish between probabilistic and physiological summation models, we measured contrast thresholds using the Visual Evoked Potential (VEP). Our previous work [2] suggests that spatial summation in the VEP is nonlinear and that it occurs preferentially for collinear configurations. Traditional probability summation models predict that areal summation will improve threshold independent of stimulus configuration. Contrast thresholds were derived from VEP contrast response functions for either circular or elongated Gabor patches with aspect ratios up to 6:1. The carrier orientation was either the same as the patch envelope orientation (collinear) or orthogonal to it. Response amplitudes were larger and contrast sensitivity was higher for collinear configurations. The results are consistent with nonlinear, configuration dependent summation that is more extensive along the axis of orientation.

Contrast Sensitivity↗
PubMed2001

Combining drug-disease and economic modelling to inform drug development decisions.

Drug-disease models and clinical trial simulations are increasingly being used to support trial design and treatment optimization decisions. Less widely recognized is their potential for guiding strategic development decisions. These decisions require economic valuation of the potential product profile of efficacy, safety, ease of use, and so on. This review presents a disguised case study that uses drug-disease modelling to generate a probabilistic forecast of a drug's profile. This allows a quantitative analysis of whether to pursue a once-a-day regimen for an antiretroviral being tested twice-a-day in Phase II trials, and if so, at what dose and for which market segments.

Journal Article↗
PubMed2005

Probabilistic neural network multiple classifier system for predicting the genotoxicity of quinolone and quinoline derivatives.

Quinolone and quinoline are known to be liver carcinogens in rodents, and a number of their derivatives have been shown to exhibit mutagenicity in the Ames test, using Salmonella typhimurium strain TA 100 in the presence of S9. Both the carcinogenicity and the mutagenicity of quinolone and quinoline derivatives, as determined by SAS, can be attributed to their genotoxicity potential. This potential, which is measured by genotoxicity tests, is a good indication of carcinogenicity and mutagenicity because compounds that are positive in these tests have the potential to be human carcinogens and/or mutagens. In this study, a collection of quinolone and quinoline derivatives' carcinogenicity is determined by qualitatively predicting their genotoxicity potential with predictive PNN (probabilistic neural network) classification models. In addition, a multiple classifier system is also developed to improve the predictability of genotoxicity. Superior results are seen with the multiple classifier system over the individual PNN classification models. With the multiple classifier system, 89.4% of the quinolone derivatives were predicted correctly, and higher predictability is seen with the quinoline derivatives at 92.2% correct. The multiple classifier system not only is able to accurately predict the genotoxicity but also provides an insight about the main determinants of genotoxicity of the quinolone and quinoline derivatives. Thus, the PNN multiple classifier system generated in this study is a beneficial contributor toward predictive toxicology in the design of less carcinogenic bioactive compounds.

Animals↗
PubMed1996

Poisson-distributed active fusion complexes underlie the control of the rate and extent of exocytosis by calcium.

We have investigated the consequences of having multiple fusion complexes on exocytotic granules, and have identified a new principle for interpreting the calcium dependence of calcium-triggered exocytosis. Strikingly different physiological responses to calcium are expected when active fusion complexes are distributed between granules in a deterministic or probabilistic manner. We have modeled these differences, and compared them with the calcium dependence of sea urchin egg cortical granule exocytosis. From the calcium dependence of cortical granule exocytosis, and from the exposure time and concentration dependence of N-ethylmaleimide inhibition, we determined that cortical granules do have spare active fusion complexes that are randomly distributed as a Poisson process among the population of granules. At high calcium concentrations, docking sites have on average nine active fusion complexes.

Animals↗
PubMed2006

Detailed analysis of the cell-inactivation mechanism by accelerated protons and light ions.

A detailed study of the biological effects of diverse quality radiations, addressing their biophysical interpretation, is presented. Published survival data for V79 cells irradiated by monoenergetic protons, helium-3, carbon and oxygen ions and for CHO cells irradiated by carbon ions have been analysed using the probabilistic two-stage model of cell inactivation. Three different classes of DNA damage formed by traversing particles have been distinguished, namely severe single-track lesions which might lead to cell inactivation directly, less severe lesions where cell inactivation is caused by their combinations and lesions of negligible severity that can be repaired easily. Probabilities of single ions forming these lesions have been assessed in dependence on their linear energy transfer (LET) values. Damage induction probabilities increase with atomic number and LET. While combined lesions play a crucial role at lower LET values, single-track damage dominates in high-LET regions. The yields of single-track lethal lesions for protons have been compared with Monte Carlo estimates of complex DNA lesions, indicating that lethal events correlate well with complex DNA double-strand breaks. The decrease in the single-track damage probability for protons of LET above approximately 30 keV microm(-1), suggested by limited experimental evidence, is discussed, together with the consequent differences in the mechanisms of biological effects between protons and heavier ions. Applications of the results in hadrontherapy treatment planning are outlined.

Animals↗
PubMed2002

Spectral analysis of distributions: finding periodic components in eukaryotic enzyme length data.

We introduce the spectral analysis of distributions (SAD), a method for detecting and evaluating possible periodicity in experimental data distributions (histograms) of arbitrary shape. SAD determines whether a given empirical distribution contains a periodic component. We also propose a system of probabilistic mixture distributions to model a histogram consisting of a smooth background together with peaks at periodic intervals, with each peak corresponding to a fixed number of subunits added together. This mixture distribution model allows us to estimate the parameters of the data and to test the statistical significance of the estimated peaks. The analysis is applied to the length distribution of eukaryotic enzymes.

Algorithms↗
PubMed2002

Comparative ab initio prediction of gene structures using pair HMMs.

We present a novel comparative method for the ab initio prediction of protein coding genes in eukaryotic genomes. The method simultaneously predicts the gene structures of two un-annotated input DNA sequences which are homologous to each other and retrieves the subsequences which are conserved between the two DNA sequences. It is capable of predicting partial, complete and multiple genes and can align pairs of genes which differ by events of exon-fusion or exon-splitting. The method employs a probabilistic pair hidden Markov model. We generate annotations using our model with two different algorithms: the Viterbi algorithm in its linear memory implementation and a new heuristic algorithm, called the stepping stone, for which both memory and time requirements scale linearly with the sequence length. We have implemented the model in a computer program called DOUBLESCAN. In this article, we introduce the method and confirm the validity of the approach on a test set of 80 pairs of orthologous DNA sequences from mouse and human. More information can be found at: http://www.sanger.ac.uk/Software/analysis/doublescan/

Algorithms↗
PubMed2004

Probabilistic representation of gene regulatory networks.

MOTIVATION: Recent experiments have established unambiguously that biological systems can have significant cell-to-cell variations in gene expression levels even in isogenic populations. Computational approaches to studying gene expression in cellular systems should capture such biological variations for a more realistic representation. RESULTS: In this paper, we present a new fully probabilistic approach to the modeling of gene regulatory networks that allows for fluctuations in the gene expression levels. The new algorithm uses a very simple representation for the genes, and accounts for the repression or induction of the genes and for the biological variations among isogenic populations simultaneously. Because of its simplicity, introduced algorithm is a very promising approach to model large-scale gene regulatory networks. We have tested the new algorithm on the synthetic gene network library bioengineered recently. The good agreement between the computed and the experimental results for this library of networks, and additional tests, demonstrate that the new algorithm is robust and very successful in explaining the experimental data. AVAILABILITY: The simulation software is available upon request. SUPPLEMENTARY INFORMATION: Supplementary material will be made available on the OUP server.

Algorithms↗
PubMed2006

Probe-level measurement error improves accuracy in detecting differential gene expression.

MOTIVATION: Finding differentially expressed genes is a fundamental objective of a microarray experiment. Numerous methods have been proposed to perform this task. Existing methods are based on point estimates of gene expression level obtained from each microarray experiment. This approach discards potentially useful information about measurement error that can be obtained from an appropriate probe-level analysis. Probabilistic probe-level models can be used to measure gene expression and also provide a level of uncertainty in this measurement. This probe-level measurement error provides useful information which can help in the identification of differentially expressed genes. RESULTS: We propose a Bayesian method to include probe-level measurement error into the detection of differentially expressed genes from replicated experiments. A variational approximation is used for efficient parameter estimation. We compare this approximation with MAP and MCMC parameter estimation in terms of computational efficiency and accuracy. The method is used to calculate the probability of positive log-ratio (PPLR) of expression levels between conditions. Using the measurements from a recently developed Affymetrix probe-level model, multi-mgMOS, we test PPLR on a spike-in dataset and a mouse time-course dataset. Results show that the inclusion of probe-level measurement error improves accuracy in detecting differential gene expression. AVAILABILITY: The MAP approximation and variational inference described in this paper have been implemented in an R package pplr. The MCMC method is implemented in Matlab. Both software are available from http://umber.sbs.man.ac.uk/resources/puma.

Algorithms↗
PubMed1997

tRNAscan-SE: a program for improved detection of transfer RNA genes in genomic sequence.

We describe a program, tRNAscan-SE, which identifies 99-100% of transfer RNA genes in DNA sequence while giving less than one false positive per 15 gigabases. Two previously described tRNA detection programs are used as fast, first-pass prefilters to identify candidate tRNAs, which are then analyzed by a highly selective tRNA covariance model. This work represents a practical application of RNA covariance models, which are general, probabilistic secondary structure profiles based on stochastic context-free grammars. tRNAscan-SE searches at approximately 30 000 bp/s. Additional extensions to tRNAscan-SE detect unusual tRNA homologues such as selenocysteine tRNAs, tRNA-derived repetitive elements and tRNA pseudogenes.

Animals↗
PubMed2006

Towards biology-oriented treatment planning in hadrontherapy.

By representing damage induction by ionising particles and its repair by the cell, the probabilistic two-stage model provides a detailed description of the main processes involved in cell killing by radiation. To link this model with issues of interest in hadron radiotherapy, a simple Bragg peak model is used. Energy-loss, its straggling and the attenuation of the primary particle fluence are represented in a simplified way, based on semi-phenomenological formulas and energy-loss tables. An effective version of the radiobiological model, considering residual (unrepaired) lesions only, is joined with the simple physical model to estimate cell survival along ions' penetration depth. The predicted survival ratios for CHO cells irradiated by carbon ions are presented, showing very good agreement with experimental data.

Animals↗
PubMed1998

Cancer genes and risk assessment.

In the radiation protection approach to risk assessment, it is assumed that cancer induction follows low-level radiation exposure in a probabilistic way. The stochastic model underlying all present risk assessment methods derives risks from cancer incidence frequencies in exposed populations and associates disease outcomes totally with the level of exposure to an environmental source. Exposure is the risk factor that affects the probability of the disease outcome. But cancer risk also reflects pre-existing underlying genetic predisposition (genetic risk factors) in individuals who are exposed. The distribution of genetic risk factors in time and space is governed by the biological and social processes involved in reproduction (biological risk factors). To include both genetic and biological risk factors in cancer risk assessment, a genetic cancer risk factors model must be developed. We tested the plausibility of the genetic cancer risk factors model by surveying all genetic disorders associated with cancer in the Online Mendelian Inheritance in Man database, determined the gene map location, if known, and attached DNA sequence information if it was available. We found 641 genetic disorders associated with cancer, of which 495 have been mapped into about 120 clusters on the human genome, and of which DNA sequence data are at least partially available for 253. From the molecular variants of various cancer risk genes that have been described, and from the breeding patterns that determine carrier frequencies in the population, we deduce that significant numbers of members of the population may carry such genes. If such carriers differ in radiogenic cancer risk from non-carriers in the population, then their variability needs to be taken into account in risk assessment models.

Chromosome Mapping↗
PubMed2005

Pitch discrimination of patterned electric stimulation.

One reason for the poor pitch performance in current cochlear-implant users may be the highly synchronized neural firing in electric hearing that lacks stochastic properties of neural firing in normal acoustic hearing. This study used three different electric stimulation patterns, jittered, probabilistic, and auditory-model-generated pulses, to mimic some aspects of the normal neural firing pattern in acoustic hearing. Pitch discrimination was measured at standard frequencies of 100, 250, 500, and 1000 Hz on three Nucleus-24 cochlear-implant users. To test the utility of the autocorrelation pitch perception model in electric hearing, one, two, and four electrodes were stimulated independently with the same patterned electric stimulation. Results showed no improvement in performance with any experimental pattern compared to the fixed-rate control. Pitch discrimination was actually worsened with the jittered pattern at low frequencies (125 and 250 Hz) than that of the control, suggesting that externally introduced stochastic properties do not improve pitch perception in electric stimulation. The multiple-electrode stimulation did not improve performance but did not degrade performance either. The present results suggest that both "the right time and the right place" may be needed to restore normal pitch perception in cochlear-implant users.

Aged↗