Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “probabilistic modelling”

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 1,441 records · Page 80Linked to original sources
PubMed2005

A cost-utility analysis of low-dose hormone replacement therapy in postmenopausal women with an intact uterus.

OBJECTIVE: The objective of this study was to evaluate the cost utility of one year's treatment with a low-dose conjugated estrogen/medroxyprogesterone acetate (CE/MPA low dose) preparation (Premique Low Dose [Wyeth Pharmaceuticals, Maidenhead, UK]), compared with a higher-dose preparation (Premique; CE/MPA [Wyeth Pharmaceuticals, Maidenhead, UK]), in postmenopausal women with an intact uterus. The evaluation captured the resource implications associated with the difference in treatment discontinuation and adverse event driven consultations in patients receiving either the low- or higher-dose preparation. This economic evaluation was conducted from the perspective of the NHS. RESEARCH DESIGN AND METHODS: A health economic model was developed to calculate the incremental cost per quality-adjusted life year (QALY) gained from treatment with a lower-dose CE/MPA combination, compared with a higher-dose CE/MPA preparation. Cohorts of 100 patients were assumed to receive either CE/MPA low dose or CE/MPA for one year. A probabilistic sensitivity analysis was used to explore whether the base case model was robust to the assumptions employed. Neither costs nor consequences were discounted because of the one year timeframe. RESULTS: In the base case, CE/MPA low dose dominates, i.e. it showed a greater health gain at a reduced cost, in both mild and severe symptom populations. These results were repeated in the sensitivity analysis, with the cost-effectiveness planes for both mild and severe symptom populations showing a greater utility at a reduced cost. CONCLUSIONS: CE/MPA low dose has been demonstrated to be a cost-effective treatment of estrogen-deficiency symptoms in postmenopausal women with an intact uterus. It has great potential for increasing the number of patients benefiting from relief of menopausal symptoms while also reducing the resource utilisation associated with managing the adverse effects associated with higher-dose HRT.

Cost-Benefit Analysis↗
PubMed2006

Heavy incense burning in temples promotes exposure risk from airborne PMs and carcinogenic PAHs.

We present the mechanistic-based exposure and risk models, appraised with reported empirical data, to assess how the human exposure to airborne particulate matters (PMs) and carcinogenic polycyclic aromatic hydrocarbons (PAHs) during heavy incense burning episodes in temples. The models integrate size-dependent PM levels inside a temple from a published exploratory study associated with a human expiratory tract (HRT) model taking into account the personal exposure levels and size distributions in the HRT. The probabilistic exposure profiles of total-PAH levels inside a temple and internal PAHs doses are characterized by a physiologically based pharmacokinetic (PBPK) model with the reconstructed dose-response relationships based on an empirical three-parameter Hill equation model, describing PAHs toxicity for DNA adducts formation and lung tumor incidence responses in human white blood cells and lung. Results show that the alveolar-interstitial (AI) region has a lower mass median diameter (0.29 microm) than that in extrathoracic (ET(1), 0.37 microm), brochial (BB, 0.36 microm) and bronchiolar (bb, 0.32 microm) regions. The 50% probability (risk=0.5) of exceeding the DNA adducts frequency (DA(f)) ratio of 1.28 (95% CI: 0.55-2.40) and 1.78 (95% CI: 0.84-2.95) for external exposure of B[a]P and B[a]P(eq), respectively. The 10% (risk=0.1) probability or more of human affected by lung tumor is approximately 7.62x10(-5)% (95% CI: 3.39x10(-5)-1.71x10(-4)%) and 3.87x10(-4)% (95% CI: 1.72x10(-4)-8.69x10(-4)%) for internal exposure of B[a]P and B[a]P(eq), respectively. Our results implicate that exposure to smoke emitted from heavy incense burning may promote lung cancer risk. Our study provides a quantitative basis for objective risk prediction of heavy incense burning exposure in temples and for evaluating the effectiveness of management.

Air Pollutants↗
PubMed2002

Exemplar and prototype models revisited: response strategies, selective attention, and stimulus generalization.

J. D. Smith and colleagues (J. P. Minda & J. D. Smith, 2001; J. D. Smith & J. P. Minda, 1998,2000; J. D. Smith, M. J. Murray, & J. P. Minda, 1997) presented evidence that they claimed challenged the predictions of exemplar models and that supported prototype models. In the authors' view, this evidence confounded the issue of the nature of the category representation with the type of response rule (probabilistic vs. deterministic) that was used. Also, their designs did not test whether the prototype models correctly predicted generalization performance. The present work demonstrates that an exemplar model that includes a response-scaling mechanism provides a natural account of all of Smith et al.'s experimental results. Furthermore, the exemplar model predicts classification performance better than the prototype models when novel transfer stimuli are included in the experimental designs.

Attention↗
PubMed1994

Analysis, classification, and coding of multielectrode spike trains with hidden Markov models.

It is shown that hidden Markov models (HMMs) are a powerful tool in the analysis of multielectrode data. This is demonstrated for a 30-electrode measurement of neuronal spike activity in the monkey's visual cortex during the application of different visual stimuli. HMMs with optimized parameters code the information contained in the spatiotemporal discharge patterns as a probabilistic function of a Markov process and thus provide abstract dynamical models of the pattern-generating process. We compare HMMs obtained from vector-quantized data with models in which parametrized output processes such as multivariate Poisson or binomial distributions are assumed. In the latter cases the visual stimuli are recognized at rates of more than 90% from the neuronal spike patterns. An analysis of the models obtained reveals important aspects of the coding of information in the brain. For example, we identify relevant time scales and characterize the degree and nature of the spatiotemporal variations on these scales.

Animals↗
PubMed1999

A generalized signal detection model to predict rational variation in base rate use.

The predominant models of rational behavior currently used to analyze a large class of experiments imply that subjects neglect or place insufficient weight on base rates when making probabilistic judgments. We argue that the evidence is inadequate for this conclusion because the models make needlessly restrictive assumptions about how base rates should be used. The restrictive assumptions stem from a misuse of Bayes' rule that ignores specific aspects of how the proportions arose. We develop a model of rational behavior that generalizes signal detection theory to reflect the environment subjects routinely face and we reexamine the relevant experimental literature. Variation observed in subjects' responses to base rate information is explained by the present rational model more fully than by extant models.

Adult↗
PubMedDate not supplied

[Determination of the direction and degree of an animal's tendency to migrate based on a theoretico-probabilistic analysis of its movements in a maza].

Using Markov chains a mathematical model of animal displacement in the final labyrinth is obtained. Direction and value of animal tendency towards migration from a given location point are reflected in the complex of absolute frequencies of the system appearing in its states. When estimating the tendency towards migration in the applied labyrith the whole complex of frequencies can be featured by its component, e. g. by the frequencies of animal appearance in the extreme labyrinth passages.

Animals↗
PubMed2003

Stochastic finite element framework for simultaneous estimation of cardiac kinematic functions and material parameters.

A stochastic finite element framework is presented for the simultaneous estimation of the cardiac kinematic functions and material model parameters from periodic medical image sequences. While existing biomechanics studies of the myocardial material constitutive laws have assumed known tissue kinematic measurements, and image analysis efforts on cardiac kinematic functions have relied on fixed constraining models of mathematical or mechanical nature, we illustrate through synthetic data that a probabilistic joint estimation strategy is needed to achieve more robust and accurate analysis of the kinematic functions and material parameters at the same time. For a particular a priori constraining material model with uncertain subject-dependent parameters and a posteriori noisy imaging based observations, our strategy combines the stochastic differential equations of the myocardial dynamics with the finite element method, and the material parameters and the imaging data are treated as random variables with known prior statistics. After the conversion to state space representation, the extended Kalman filtering procedures are adopted to linearize the equations and to provide the joint estimates in an approximate optimal sense. The estimation bias and convergence issues are addressed, and we conclude experimentally that it is possible to adopt this biomechanical model based multiframe estimation approach to achieve converged estimates because of the periodic nature of the cardiac dynamics. The effort is validated using synthetic data sequence with known kinematics and material parameters. Further, under linear elastic material model, estimation results using canine magnetic resonance phase contrast image sequences are presented, which are in very good agreement with histological tissue staining results, the current gold standards.

Animals↗
PubMed2006

Probabilistic study of well capture zones distribution at the Lauswiesen field site.

The delineation of well capture zones is of utmost environmental and engineering relevance as pumping wells are commonly used both for drinking water supply needs, where protection zones have to be defined, and for investigation and remediation of contaminated aquifers. We analyze the probabilistic nature of well capture zones within the well field located at the "Lauswiesen" experimental site. The test site is part of an alluvial heterogeneous aquifer located in the Neckar river valley, close to the city of Tübingen in South-West Germany. We explore the effect of different conceptual models of the structure of aquifer heterogeneities on the delineation of three-dimensional probabilistic well catchment and time-related capture zones, in the presence of migration of conservative solutes. The aquifer is modeled as a three-dimensional, doubly stochastic composite medium, where distributions of geo-materials and hydraulic properties are uncertain. We study the relative importance of uncertain facies geometry and uncertain hydraulic conductivity and porosity on predictions of catchment and solute time of travel to the pumping well by focusing on cases in which (1) the facies distribution is random, but the hydraulic properties of each material are fixed, and (2) both facies geometry and material properties vary stochastically. The problem is tackled within a conditional numerical Monte Carlo framework. Results are provided in terms of probabilistic demarcations of the three-dimensional well catchment and time-related capture zones. Our findings suggest that the uncertainty associated with the prediction of the location of the outer boundary of well catchment at the "Lauswiesen" site is significantly affected by the conceptual model adopted to incorporate the heterogeneous nature of the aquifer domain in a predictive framework. Taking into account randomness of both lithofacies distribution and materials hydraulic conductivity allows recognizing the existence of preferential flow paths that influence the extent of the well catchment and the solute travel time distribution at the site.

Computer Simulation↗
PubMed2006

A Bayesian belief network for quality assessment: application to employment officer support.

BACKGROUND: 'Supported' employment stipulates that disabled people should have real jobs for real pay. This paper models kinds of supported employment, assesses how the support and placement features affect its outcomes and its quality from the perspective of the employees, and provides a dynamic model to help explore what types of interventions might promote greater social inclusion for people with learning and other disabilities. METHOD: Bayesian belief networks (BBNs) provide the general framework for modelling the relationships between the variables and features of interest. The structure, probabilistic specification and quality indicators were elicited from project advisory groups, including people with learning disability, and took into account a pilot survey of 30 individuals. A subsequent survey of 1,461 supported employees was used to update the model and to provide actual assessments of quality of placement. RESULTS: We present the BBN methodology in some detail, as novel to this discipline. We show how the model was constructed, and its implications for supported employment. We derive indices for quality of placement, taking into account the views of clients. We show how survey and individual results can be used to update the model. Use of the model suggests that quality of placement is, on average, relatively high, with small differences between groups with differing primary disability. CONCLUSIONS: The BBN is the appropriate methodology to model complex relationships and interventions for problems such as these. The model developed in this study can be used to assess and improve the fit between people and jobs, both at the individual level and for groups of employees, and can take into account different kinds of quality for different stakeholders.

Adult↗
PubMed1999

Recognition of handwritten similar Chinese characters by self-growing probabilistic decision-based neural network.

Recognition of similar (confusion) characters is a difficult problem in optical character recognition (OCR). In this paper, we introduce a neural network solution that is capable of modeling minor differences among similar characters, and is robust to various personal handwriting styles. The Self-growing Probabilistic Decision-based Neural Network (SPDNN) is a probabilistic type neural network, which adopts a hierarchical network structure with nonlinear basis functions and a competitive credit-assignment scheme. Based on the SPDNN model, we have constructed a three-stage recognition system. First, a coarse classifier determines a character to be input to one of the pre-defined subclasses partitioned from a large character set, such as Chinese mixed with alphanumerics. Then a character recognizer determines the input image which best matches the reference character in the subclass. Lastly, the third module is a similar character recognizer, which can further enhance the recognition accuracy among similar or confusing characters. The prototype system has demonstrated a successful application of SPDNN to similar handwritten Chinese recognition for the public database CCL/HCCR1 (5401 characters x200 samples). Regarding performance, experiments on the CCL/HCCR1 database produced 90.12% recognition accuracy with no rejection, and 94.11% accuracy with 6.7% rejection, respectively. This recognition accuracy represents about 4% improvement on the previously announced performance. As to processing speed, processing before recognition (including image preprocessing, segmentation, and feature extraction) requires about one second for an A4 size character image, and recognition consumes approximately 0.27 second per character on a Pentium-100 based personal computer, without use of any hardware accelerator or co-processor.

China↗
PubMed2005

Inferring genetic regulatory logic from expression data.

MOTIVATION: High-throughput molecular genetics methods allow the collection of data about the expression of genes at different time points and under different conditions. The challenge is to infer gene regulatory interactions from these data and to get an insight into the mechanisms of genetic regulation. RESULTS: We propose a model for genetic regulatory interactions, which has a biologically motivated Boolean logic semantics, but is of a probabilistic nature, and is hence able to confront noisy biological processes and data. We propose a method for learning the model from data based on the Bayesian approach and utilizing Gibbs sampling. We tested our method with previously published data of the Saccharomyces cerevisiae cell cycle and found relations between genes consistent with biological knowledge.

Bayes Theorem↗
PubMed2004

Prediction error during retrospective revaluation of causal associations in humans: fMRI evidence in favor of an associative model of learning.

Associative learning theory assumes that prediction error is a driving force in learning. A competing view, probabilistic contrast (PC) theory, is that learning and prediction error are unrelated. We tested a learning phenomenon that has proved troublesome for associative theory--retrospective revaluation--to evaluate these two models. We previously showed that activation in right lateral prefrontal cortex (PFC) provides a reliable signature for the presence of prediction error. Thus, if the associative view is correct, retrospective revaluation should be accompanied by right lateral PFC activation. PC theory would be supported by the absence of this activation. Right PFC and ventral striatal activation occurred during retrospective revaluation, supporting the associative account. Activations appeared to reflect the degree of revaluation, predicting later brain responses to revalued cues. Our results support a modified associative account of retrospective revaluation and demonstrate the potential of functional neuroimaging as a tool for evaluating competing learning models.

Adult↗
PubMed2005

Material sensitivity study on lumbar motion segment (L2-L3) under sagittal plane loadings using probabilistic method.

OBJECTIVE: In this study, the probabilistic responses of a three-dimensional finite element L2-L3 motion segment, with and without posterior elements, tested under sagittal plane loadings, are presented. Understanding the effect of biologic uncertainties and variations on the biomechanical response provides an insight into spinal behavior under normal and degenerated conditions. METHODS: The biologic variability of 19 spinal components (nucleus, annulus, ligament, cortical/cancellous bone, endplate, and ligaments) in the motion segment was incorporated using statistical distributions into the model. A total of 2000 runs were performed using Monte Carlo probabilistic algorithms to compute the probabilistic response. RESULTS: This study establishes the relative importance of the spinal components in resisting the loading modes. The results show that for an intact motion segment, posterior ligaments are more dominant than intervertebral disc in resisting flexion moment. In extension, the capsular ligaments were found to be the most influential parameter. The intervertebral disc (ie, nucleus and annulus) affects the angular response of the disc body segment more than the hard tissues (ie, cortical and cancellous bone). CONCLUSIONS: The application of the probabilistic analysis provides a new approach whereby the influences of inherent uncertainties and variations in biologic structures can be studied and the biomechanical response assessed.

Finite Element Analysis↗
PubMed2006

Application of cattle manure as fertilizer in pastureland: estimating the incremental risk due to metal accumulation employing a multicompartment model.

Specific-site data of metal concentration in cattle manure from NW Spain and a multicompartment fate and exposure model were used to evaluate metal fate and the main routes of exposure after a 100 year period of application of cattle manure as fertiliser in pastureland. Risk assessment was performed as a probabilistic analysis, and using a conservative worst-case exposure scenario. An accumulation model was used to predict the metal concentration in each environmental medium of concern. The incremental risk was estimated for the population inhabiting the surroundings of the area by a general multiexposure model. Monte Carlo simulations were performed to analyse uncertainty of the results. Furthermore, a sensitivity analysis was carried out to identify the contribution to variance by the different metals and exposure routes. Among the five pathways evaluated, the ingestion of meat and milk from cattle grazing in the area represents the main contribution to total exposure. The results indicate that the incremental risk to human health for people living in the surroundings of pasturelands due to continuous application of cattle manure after a 100 year period are not negligible for the metals considered (Cd, Cu, Ni, Pb and Zn), posing a total Reasonable Maximum Exposure (RME) of 0.75, being the ingestion of meat the main exposure pathway.

Agriculture↗
PubMed2003

A basin-specific aquatic food web biomagnification model for estimation of mercury target levels.

In the Willamette River Basin (WRB, Oregon, USA), health advisories currently limit consumption of fish that have accumulated methylmercury (MeHg) to levels posing a potential health risk for humans. Under the Clean Water Act, these advisories create the requirement for a total maximum daily load (TMDL) for mercury in the WRB. A TMDL is a calculation of the maximum amount of a pollutant that a body of water can receive and still meet water-quality standards. Because MeHg is known to biomagnify in aquatic food webs, a basin-specific biomagnification factor can be used, given a protective fish tissue criterion, to estimate total mercury concentrations in surface waters required to lower advisory mercury concentrations currently in fish in the WRB. This paper presents an aquatic food web biomagnification model that simulates inorganic mercury (Hg(II)) and MeHg accumulation in fish tissue and estimates WRB-specific biomagnification factors for resident fish species of concern to stakeholders. Probabilistic (two-dimensional Monte Carlo) techniques propagate parameter variability and uncertainty throughout the model, providing decision makers with credible range information and increased flexibility in establishing a specific mercury target level. The model predicts the probability of tissue mercury concentrations in eight fish species within the range of concentrations measured in these species over 20 years of water-quality monitoring. Estimated mean biomagnification factor values range from 1.12 x 10(6) to 7.66 x 10(6) and are within the range of U.S. Environmental Protection Agency national values. Several WRB-specific mercury target levels are generated, which very by their probability of affording human health protection relative to the federal MeHg tissue criterion of 0.30 mg/kg. Establishing a specific numeric target level is, however, a public policy decision, and one that will require further discussions among WRB stakeholders.

Animals↗
PubMed1999

An experimental study on estimating human error probability (HEP) parameters for PSA/HRA by using human model simulation.

A framework of Human Error Probability (HEP) parameters, which is needed for Human Reliability Analysis (HRA) within a practice of Probabilistic Safety Assessment (PSA) of Nuclear Power Plant is first proposed. Then a laboratory experiment was conducted in order to construct a computer simulation model (human model) that describes human cognitive behaviour on detecting and diagnosing plant anomaly causes. An inter-comparison between experimental data and human model simulation was performed to estimate Human Cognitive Reliability (HCR) curves, in order to confirm the applicability of a human model for estimating these HEP parameters for PSA/HRA practice.

Cognition↗
PubMed1997

DIAS--the diabetes advisory system: an outline of the system and the evaluation results obtained so far.

The present paper gives a description of the Diabetes Advisory System (DIAS), and the evaluation results obtained so far. DIAS is a decision support system for the management of insulin dependent diabetes. The core of the system is a compartment model of the human carbohydrate metabolism implemented as a causal probabilistic network (CPN or Bayesian network), which gives it the ability to handle the uncertainty, for example, in blood glucose measurements or physiological variations in glucose metabolism. The evaluation results suggest that, at least in our hands, DIAS can generate advice that is safe and of a quality that is at least comparable to what is available from experienced clinicians.

Bayes Theorem↗
PubMed2026

Implicit and explicit statistical learning in reading: Evidence from a randomized controlled-learning study and computational modeling.

A key challenge in reading acquisition is understanding how learners extract the complex probabilistic mappings between print, meaning, and sound. Statistical learning (SL) theory offers a mechanistic account of how such mappings are acquired, whether implicitly through exposure or explicitly through instruction. We conducted a randomized controlled-learning study in Chinese, a writing system characterized by multiple sub-lexical regularities linking orthography, semantics, and phonology. Ninety-five 2nd-3rd graders with or at risk for dyslexia were randomly assigned to one of three groups: an implicit-SL training group exposed to repeated lexical and sublexical orthography-semantics-phonology associations, an explicit-SL training group receiving the same input plus explicit instruction on the sublexical print-sound mapping, and a no-SL control group. Both SL groups outperformed controls on the characters they were trained on, as well as on untrained characters that required generalization. However, only the explicit group demonstrated abstraction of print-sound mapping to novel items. Neural network simulations further revealed distinct mechanisms supporting implicit and explicit SL, consistent with a dual-system account of reading acquisition. Together, these findings (1) clarify how implicit and explicit learning distinctly support the discovery of statistical structure in written language and (2) underscore the implicit-explicit dual learning mechanism underlying reading acquisition.

Humans↗