PubMed Health⌕ Search

SEARCH · PubMed Health

Results for “Uncertainty modelling”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

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

At least 73 records · Page 4Linked to original sources
PubMed2006

Integrated urban water modelling with uncertainty analysis.

In the last twenty years, the scientific world has paid particular care towards the problems that involve the environment. Accordingly, several researches were developed to describe phenomena that take place during both wet and dry periods and to increase the knowledge in this field. In particular, attention was addressed towards the problems linked with receiving water body pollution because of the impact of rain water in the urban environment. In order to obtain a good description of the problem, it is important to analyse both quantity and quality aspects connected with all the transformation phases that characterise the urban water cycle. Today, according to this point, integrated modelling approach is spreading, aiming to find solutions to improve the quality characteristics of the receiving water body. Because several models are connected together for analysing the fate of pollutants from the sources on the urban catchment to the final recipient, classical problems connected with the selection and calibration of parameters are amplified by the complexity of the modelling approach increasing the uncertainty and reducing the reliability connected with a model's application. For this reason, a parsimonious integrated modelling approach has been developed and its uncertainty has been evaluated adopting the well known GLUE framework. For the purpose of the study, the uncertainty analysis has been applied to a "semi-hypothetic" case study obtained connecting Fossolo catchment (Bologna-Italy) to the Oreto river near Palermo (Italy).

Cities↗
PubMed2003

Limitations of a convolution method for modeling geometric uncertainties in radiation therapy. II. The effect of a finite number of fractions.

Convolution methods can be used to model the effect of geometric uncertainties on the planned dose distribution in radiation therapy. This requires several assumptions, including that the patient is treated with an infinite number of fractions, each delivering an infinitesimally small dose. The error resulting from this assumption has not been thoroughly quantified. This is investigated by comparing dose distributions calculated using the Convolution method with the result of Stochastic simulations of the treatment. Additionally, the dose calculated using the conventional Static method, a Corrected Convolution method, and a Direct Simulation are compared to the Stochastic result. This analysis is performed for single beam, parallel opposed pair, and four-field box techniques in a cubic water phantom. Treatment plans for a simple and a complex idealized anatomy were similarly analyzed. The average maximum error using the Static method for a 30 fraction simulation for the three techniques in phantoms was 23%, 11% for Convolution, 10% for Corrected Convolution, and 10% for Direct Simulation. In the two anatomical examples, the mean error in tumor control probability for Static and Convolution methods was 7% and 2%, respectively, of the result with no uncertainty, and 35% and 9%, respectively, for normal tissue complication probabilities. Convolution provides superior estimates of the delivered dose when compared to the Static method. In the range of fractions used clinically, considerable dosimetric variations will exist solely because of the random nature of the geometric uncertainties. However, the effect of finite fractionation appears to have a greater impact on the dose distribution than plan evaluation parameters.

Algorithms↗
PubMed1997

Non-parametric deconvolution provides an objective assessment of GH responsiveness to GH-releasing stimuli in normal subjects.

OBJECTIVE: Deconvolution analysis has been proposed as an effective method for analysing the physiology of GH secretion. In the literature, it has been applied to spontaneous secretion data characterized by long and uniform sampling paradigms. In the present study we investigated the applicability of non-parametric deconvolution to the analysis of response-to-stimuli (RTS) data characterized by infrequent and non-uniform sampling. PATIENTS: Thirty-six healthy adult male volunteers (age range 24-37 years) were randomly subdivided into two groups (group I, n = 30; group II, n = 6). DESIGN: Subjects of group I were tested with a single 1 microgram/kg body weight GH-releasing hormone (GHRH) bolus, administered at 0 minutes. Subjects of group II were tested, in random order, with a 4- or 5-day interval, with (1) two consecutive 1 microgram/kg body weight GHRH boluses at 0 and 120 minutes and (2) two consecutive 1 microgram/kg body weight hexarelin boluses, administered at 0 and 120 minutes. MEASUREMENTS: GH levels were determined at 0, 15, 30, 45, 60, 90 and 120 minutes (group I) and -30, 0, 15, 30, 45, 60, 120, 135, 150, 165, 180 and 240 minutes (group II). A numerically efficient regularization-based non-parametric deconvolution algorithm incorporating non-negativity constraints was used to estimate the time profile of the instantaneous secretion rate (ISR). Confidence limits allowing for both measurement error and kinetic model uncertainty were computed using a Monte-Carlo procedure. In order to validate the deconvolution method, a simulated benchmark problem was set up. RESULTS: The analysis of the benchmark problem showed that the proposed method is capable of providing an accurate reconstruction of the ISR (as measured by the root mean square (RMS) error). Moreover, it appeared that reliable confidence limits cannot be obtained unless the kinetic model uncertainty is taken into account. The analysis of the data showed a clear rise in the ISR subsequent to the first bolus (either GHRH or hexarelin), with most of the response occurring within 60 minutes of the stimulus. In group I, it was also seen that discarding the samples collected at times 90 and 120 minutes only marginally affected the estimate of the cumulated ISR over 0-60 minutes (the variation was always less than 3%). The analysis of GH responsiveness to repeated stimuli (group II) showed that the amount of hormone secreted after the second bolus was clearly reduced in comparison with the elicited by the first stimulus, most of the response occurring within 60 minutes of the injection. The amount of GH secreted after the second stimulus ranged from 13 to 36% (GHRH 17-36%; hexarelin 13-36%) of the overall amount of hormone secreted after time 0 minutes. CONCLUSIONS: Even with relatively few samples, non-parametric deconvolution of response-to-stimulus data is capable of providing a reliable, smooth and non-negative estimate of the GH instantaneous secretion rate that offers a realistic representation of the GH secretory dynamics. The non-parametric approach compares favourably with respect to discrete deconvolution methods, that yield discontinuous instantaneous secretion rates profiles, and parametric methods that would require more stringent assumptions on the shape of the instantaneous secretion rate. When assessing confidence limits it is essential to take into account both measurement error and kinetic model uncertainty. Using deconvolution in normal subjects, the estimated instantaneous secretion rate between 0 and 60 minutes is scarcely affected by samples taken after time 60 minutes. Since most of the secretory response takes place during this time interval, there is motivation for investigating the use of shorter sampling protocols in conjunction with deconvolution analysis. Although pulse detection and the assessment of the shape of spontaneous pulses have not been investigated, it could be interesting to apply non-parametric deconvolution to spontaneous sec

Adult↗
PubMed2004

Limitations of a convolution method for modeling geometric uncertainties in radiation therapy: the radiobiological dose-per-fraction effect.

The convolution method can be used to model the effect of random geometric uncertainties into planned dose distributions used in radiation treatment planning. This is effectively done by linearly adding infinitesimally small doses, each with a particular geometric offset, over an assumed infinite number of fractions. However, this process inherently ignores the radiobiological dose-per-fraction effect since only the summed physical dose distribution is generated. The resultant potential error on predicted radiobiological outcome [quantified in this work with tumor control probability (TCP), equivalent uniform dose (EUD), normal tissue complication probability (NTCP), and generalized equivalent uniform dose (gEUD)] has yet to be thoroughly quantified. In this work, the results of a Monte Carlo simulation of geometric displacements are compared to those of the convolution method for random geometric uncertainties of 0, 1, 2, 3, 4, and 5 mm (standard deviation). The alpha/betaCTV ratios of 0.8, 1.5, 3, 5, and 10 Gy are used to represent the range of radiation responses for different tumors, whereas a single alpha/betaOAR ratio of 3 Gy is used to represent all the organs at risk (OAR). The analysis is performed on a four-field prostate treatment plan of 18 MV x rays. The fraction numbers are varied from 1-50, with isoeffective adjustments of the corresponding dose-per-fractions to maintain a constant tumor control, using the linear-quadratic cell survival model. The average differences in TCP and EUD of the target, and in NTCP and gEUD of the OAR calculated from the convolution and Monte Carlo methods reduced asymptotically as the total fraction number increased, with the differences reaching negligible levels beyond the treatment fraction number of > or =20. The convolution method generally overestimates the radiobiological indices, as compared to the Monte Carlo method, for the target volume, and underestimates those for the OAR. These effects are interconnected and attributed to assuming an infinite number of fractions inherent in the implementation of the convolution technique, irrespective of the uniqueness of each treatment schedule. Based on the fraction numbers analyzed (1-50), and the range of fraction numbers normally used clinically (> or =20), the convolution method can be used safely to estimate the effects of random geometric uncertainties on prostate treatment radiobiological outcomes, for both the target and the OAR. Although the results of this study is likely to apply to other clinical sites and treatment techniques other than the four-field, further validation similar to those done in this study may be necessary prior to clinical implementation.

Algorithms↗
PubMed2002

Geographic origin of human mitochondrial DNA: accommodating phylogenetic uncertainty and model comparison.

Many biogeographic problems are tested on phylogenetic trees. Typically, the uncertainty in the phylogeny is not accommodated when investigating the biogeography of the organisms. Here we present a method that accommodates uncertainty in the phylogenetic trees. Moreover, we describe a simple method for examining the support for competing biogeographic scenarios. We illustrate the method using mitochondrial DNA sequences sampled from modern humans. The geographic origin of modern human mtDNA is inferred to be in Africa, although support for this hypothesis was ambiguous for data from an early paper.

Africa↗
PubMed1994

A dynamic migration model with uncertainty.

The author presents "a dynamic version of the Harris-Todaro migration model where a finite population of infinitely-lived Bayesian agents choose consumption and migration decision rules as a function of their histories. The agents do not know the production functions in the two sectors and learn about them through wage draws that they receive from the stochastic production functions. The government knows the true production functions but is uninformed about the agents' beliefs, and the actual wage draws they observe. The government maximizes its welfare function using wage subsidies in the two sectors, and a migration tax. We solve the agents' dynamics programming problem, and then use the solution to solve the government's dynamic programming problem. We study the effects of government policies on the population distribution, and illustrate the model by numerically solving a particular parametric example."

Demography↗
PubMed2005

Model averaging using the Kullback information criterion in estimating effective doses for microbial infection and illness.

Since the National Food Safety Initiative of 1997, risk assessment has been an important issue in food safety areas. Microbial risk assessment is a systematic process for describing and quantifying a potential to cause adverse health effects associated with exposure to microorganisms. Various dose-response models for estimating microbial risks have been investigated. We have considered four two-parameter models and four three-parameter models in order to evaluate variability among the models for microbial risk assessment using infectivity and illness data from studies with human volunteers exposed to a variety of microbial pathogens. Model variability is measured in terms of estimated ED01s and ED10s, with the view that these effective dose levels correspond to the lower and upper limits of the 1% to 10% risk range generally recommended for establishing benchmark doses in risk assessment. Parameters of the statistical models are estimated using the maximum likelihood method. In this article a weighted average of effective dose estimates from eight two- and three-parameter dose-response models, with weights determined by the Kullback information criterion, is proposed to address model uncertainties in microbial risk assessment. The proposed procedures for incorporating model uncertainties and making inferences are illustrated with human infection/illness dose-response data sets.

Food Microbiology↗
PubMed2005

Prostate cancer, the PSA test and academic detailing in Australian general practice: an economic evaluation.

OBJECTIVES: To evaluate whether introduction of a national education program for GPs to improve decision making relating to the use of prostate specific antigen (PSA) testing for screening represents 'value-for-money' from the perspective of the Australian Government. METHODS: The annual equivalent costs and consequences of a proposed national program in steady state operation are estimated for Australia using 1996 as the reference year. Because of the controversy about the efficacy of screening using PSA testing, two scenarios are modelled. Uncertainty in the model is examined using Monte Carlo simulation methods. RESULTS: In scenario one, our model predicts that the national program would cost dollars 12.5 million (gross) or dollars 6.6 million (net), would reduce the burden of disease by 4.7% of total DALYs due to prostate cancer in those aged 70 and over, with no loss of life and an incremental cost effectiveness ratio (ICER) of dollars 16,000/DALY (gross) and dollars 8,500/DALY (net). In scenario two, the proposed program would cost dollars 12.5 million (gross) or dollars 7.1 million (net), would reduce the burden of disease by 3.1% of total, increase by 44 the prostate cancer deaths at an ICER of dollars 24,000/DALY (gross) and dollars 14,000/DALY (net). CONCLUSIONS: These findings, with an overall health benefit at moderate cost and acceptable ICER, support the case for consideration of a national education program on the assumption that prostate cancer screening over age 70 does not reduce mortality. A larger Australian study currently being conducted should provide stronger evidence on the value of implementing a full national program.

Australia↗
PubMed2003

Uncertainties in modeling secondary organic aerosols: three-dimensional modeling studies in Nashville/western Tennessee.

The formation of secondary organic aerosols (SOA) is simulated for the Nashville/western Tennessee domain using three recent SOA modules incorporated into the three-dimensional air quality model, CMAQ. The Odum/Griffin et al. and CMU/STI modules represent SOA absorptive partitioning into a mixture of primary and secondary particulate organic compounds (OC), with some differences in the formulation of the absorption process and the selection of SOA species and their precursors. Empirical representations based on measured laboratory SOA yields are used for condensable organic products in both these modules. The AEC module simulates SOA absorption into organic and aqueous particulate phases, and a representation based on an explicit gas-phase mechanism is used in the AEC module. Predicted SOA concentrations can vary by a factor of 10 or more. In general, the gas-phase mechanistic approach predicts a higher yield of SOA than those based on laboratory yields. There exist some differences in the two empirical modules despite their similar basis on experimental data. All three modules predict a dominance of SOA of biogenic origin as compared to SOA of anthropogenic origin. The causes for differences among the three SOA modules include the representation of terpenes, the mechanistic versus empirical representation of SOA-forming reactions, the identities of SOA, and the parameters used in the gas/particle partitioning calculations. Two sensitivity studies show that formation of water-soluble SOA and temperature dependence may be areas of key uncertainties affecting current models.

Aerosols↗
PubMed2005

Impact of dimension uncertainty and model calibration on sewer system assessment.

Assessments of sewer performance are usually based on a single computation of CSO (combined sewer overflow) volumes using a time series of rainfall as system loads. A shortcoming of this method is that uncertainties in knowledge of sewer system dimensions are not taken into account. Moreover, sewer models are rarely calibrated. This paper presents the impacts of database errors and model calibration on return periods of calculated CSO volumes. The impact of uncertainties is illustrated with two examples. Variability of calculated CSO volumes is estimated using Monte Carlo simulations. The results show that calculated CSO volumes vary considerably due to database errors, especially uncertain dimensions of the catchment area. Furthermore, event-based calibration of a sewer model does not result in more reliable predictions because the calibrated parameters have low portability. However, it enables removal of database errors harmonising model predictions and 'reality'.

Calibration↗
PubMed1998

Effect of conductivity uncertainties and modeling errors on EEG source localization using a 2-D model.

This paper presents a sensitivity study of electroencephalography-based source localization due to errors in the head-tissue conductivities and to errors in modeling the conductivity variation inside the brain and scalp. The study is conducted using a two-dimensional (2-D) finite element model obtained from a magnetic resonance imaging (MRI) scan of a head cross section. The effect of uncertainty in the following tissues is studied: white matter, gray matter, cerebrospinal fluid (CSF), skull, and fat. The distribution of source location errors, assuming a single-dipole source model, is examined in detail for different dipole locations over the entire brain region. We also present a detailed analysis of the effect of conductivity on source localization for a four-layer cylinder model and a four-layer sphere model. These two simple models provide insight into how the effect of conductivity on boundary potential translates into source location errors, and also how errors in a 2-D model compare to errors in a three-dimensional model. Results presented in this paper clearly point to the following conclusion: unless the conductivities of the head tissues and the distribution of these tissues throughout the head are modeled accurately, the goal of achieving localization accuracy to within a few millimeters is unattainable.

Brain↗
PubMed2006

Lung cancer attributable to indoor radon exposure in france: impact of the risk models and uncertainty analysis.

OBJECTIVE: The inhalation of radon, a well-established human carcinogen, is the principal-and omnipresent-source of radioactivity exposure for the general population of most countries. Scientists have thus sought to assess the lung cancer risk associated with indoor radon. Our aim here is to assess this risk in France, using all available epidemiologic results and performing an uncertainty analysis. METHODS: We examined the exposure-response relations derived from cohorts of miners and from joint analyses of residential case-control studies and considered the interaction between radon and tobacco. The exposure data come from measurement campaigns conducted since the beginning of the 1980s by the Institute for Radiation Protection and Nuclear Safety and the Directorate-General of Health in France. We quantified the uncertainties associated with risk coefficients and exposures and calculated their impact on risk estimates. RESULTS: The estimated number of lung cancer deaths attributable to indoor radon exposure ranges from 543 [90% uncertainty interval (UI) , 75-1,097] to 3,108 (90% UI, 2,996-3,221) , depending on the model considered. This calculation suggests that from 2.2% (90% UI, 0.3-4.4) to 12.4% (90% UI, 11.9-12.8) of these deaths in France may be attributable to indoor radon. DISCUSSION: In this original work we used different exposure-response relations from several epidemiologic studies and found that regardless of the relation chosen, the number of lung cancer deaths attributable to indoor radon appears relatively stable. Smokers can reduce their risk not only by reducing their indoor radon concentration but also by giving up smoking.

Adult↗
PubMed1996

Predictions of the nuclear activation of materials on LDEF produced by the space radiation environment and comparison with flight measurements.

Model calculations have been made to compare with the induced radioactivity measured for materials on the LDEF satellite. Predictions and data comparisons are made for aluminum spacecraft components and for vanadium and nickel samples placed at multiple locations on the spacecraft. The calculated vs observed activations provide an indication of present model uncertainties in predicting nuclear activation as well as the magnitude and directionality of the trapped proton environment for low-Earth orbit missions. Environment model uncertainties based on the activation measurements are consistent with the uncertainties evaluated using other LDEF radiation dosimetry data.

Anisotropy↗
PubMed2003

Choice of model and uncertainties of the gamma-ray and neutron dosimetry in relation to the chromosome aberrations data in Hiroshima and Nagasaki.

Chromosome data pertaining to blood samples from 1,703 survivors of the Hiroshima and Nagasaki A-bombs, were utilized and different models for chromosome aberration dose response investigated. Models applied included those linear or linear-quadratic in equivalent dose. Models in which neutron and gamma doses were treated separately (LQ-L model) were also used, which included either the use of a low-dose limiting value for the relative biological effectiveness (RBE) of neutrons of R(0)=70+/-10 or an RBE value of R(1)=15+/-5 at 1 Gy. The use of R(1) incorporates the assumption that it is much better known than R(0), with much less associated uncertainty. In addition, error-reducing transformations were included which were found to result in a 50% reduction of the standard error associated with one of the model fit parameters which is associated with the proportion of cells with at least one aberration, at 1 Gy gamma dose. Several justifiable modifications to the DS86 doses according to recent nuclear retrospective dosimetry measurements were also investigated. Gamma-dose modifications were based on published thermoluminescence measurements of quartz samples from Hiroshima and on a tentative reduction for Nagasaki factory worker candidates by a factor of 0.6. Neutron doses in Hiroshima were modified to become consistent with recent fast neutron activation data based on copper samples. The applied dose modifications result in an increase in non-linearity of the dose-response curve for Hiroshima, and a corresponding decrease in that for Nagasaki, an effect found to be most pronounced for the LQ-L models investigated. As a result the difference in the dose-response curves observed for both cities based on DS86 doses, is somewhat reduced but cannot be entirely explained by the dose modifications applied. The extent to which the neutrons contribute to chromosome aberration induction in Hiroshima depends significantly on the model used. The LQ-L model including an R(1) value of 15 at 1 Gy which is recommended here, would predict between 10% and 20% of the observed chromosome aberrations to be due to neutrons, at all doses. Because of the good agreement between DS86 predictions and the results of retrospective gamma and neutron dosimetry, the modifications applied here to DS86 doses are relatively small. Consequently, the choices of model and RBE values were found to be the major factors dominating the interpretation of the chromosome data for Hiroshima and Nagasaki, with the dose modifications resulting in a smaller influence.

Bone Marrow↗
PubMed2000

A radioiodine speciation, deposition, and dispersion model with uncertainty propagation for the Oak Ridge dose reconstruction.

Between 1944 and 1956, radioactive 131I was released into the atmosphere from operations at the Oak Ridge National Laboratory in Oak Ridge, TN. The releases occurred from stacks and from building vents and openings in three different chemical forms: elemental, organic, and particulate. During their transport in the atmosphere, different forms of iodine react differently with other atmospheric chemicals and moisture, and are removed from the plume at different rates by the processes of dry and wet deposition. A modified Gaussian plume model was developed to address the processes of radioiodine speciation, deposition, depletion, and dispersion in the atmosphere, and to propagate uncertainties in input parameter values through to the ground-level concentrations of 131I in air. A unique approach was used to develop an implicitly correlated set of hourly meteorological parameters for any day of a month for each month of the year from ten years of available data between 1987 and 1996. The model was validated for both annual average and short-term releases. For the annual average releases, the predictions of ground-level concentrations of 131I from the model were within a factor of 2 of measured field data. For two of the three sets of available weekly data, the measurements fell within the 95% subjective confidence interval of model predictions. Predictions of ground-level air concentrations were made on an annual average basis for the entire period of release and on a short-term, episodic basis for a 1954 accident.

Atmosphere↗
PubMed2006

Adaptive dynamic surface control of flexible-joint robots using self-recurrent wavelet neural networks.

A new method for the robust control of flexible-joint (FJ) robots with model uncertainties in both robot dynamics and actuator dynamics is proposed. The proposed control system is a combination of the adaptive dynamic surface control (DSC) technique and the self-recurrent wavelet neural network (SRWNN). The adaptive DSC technique provides the ability to overcome the "explosion of complexity" problem in backstepping controllers. The SRWNNs are used to observe the arbitrary model uncertainties of FJ robots, and all their weights are trained online. From the Lyapunov stability analysis, their adaptation laws are induced, and the uniformly ultimately boundedness of all signals in a closed-loop adaptive system is proved. Finally, simulation results for a three-link FJ robot are utilized to validate the good position tracking performance and robustness against payload uncertainties and external disturbances of the proposed control system.

Journal Article↗
PubMed2006

Uncertainty of calculation results in vehicle collision analysis.

In the analysis of road accidents two types of calculation result uncertainty can be distinguished: modelling uncertainty and uncertainty in calculation results [R.M. Brach, M. Brach, Vehicle Accident Analysis & Reconstruction Methods, SAE International Publisher, Warrendale, 2005]. The problem becomes very important first of all when minor modifications of input parameters or application of different models of the phenomenon lead to a fundamentally different answer to the question posed by the court. The aim of the paper was to prove the necessity of including the problem of uncertainty in calculations related to vehicle collision mechanics and to justify the application of different error analysis methods recommendable in vehicle collision reconstruction. The data file from crash test No. 7 [H. Burg, M. Lindenmann, Unfallversuche, Verlag Information Ambs, Kippenheim, 1982] was used, the selection restricted to the range typical of average police records of collision place. Collision speeds were calculated using two methods: reconstruction and simulation. The analysis of uncertainty was carried out. Maximum and mean square uncertainty were calculated by means of total differential of relevant forms. Since the reconstruction resulted in very broad error intervals of uniform distribution, additional calculations were performed by the Monte Carlo method using algorithm described in [W. Wach, J. Unarski, Determination of vehicle velocities and collision location by means of Monte Carlo simulation method, Special Publication Accident Reconstruction SP-1999, SAE Paper No. 2006-01-0907, 2006].

Journal Article↗