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At least 487 records · Page 27Linked to original sources

PubMed2000

Tissue segmentation on MR images of the brain by possibilistic clustering on a 3D wavelet representation.

An algorithm for the segmentation of a single sequence of three-dimensional magnetic resonance (MR) images into cerebrospinal fluid, gray matter, and white matter classes is proposed. This new method is a possibilistic clustering algorithm using the fuzzy theory as frame and the wavelet coefficients of the voxels as features to be clustered. Fuzzy logic models the uncertainty and imprecision inherent in MR images of the brain, while the wavelet representation allows for both spatial and textural information. The procedure is fast, unsupervised, and totally independent of any statistical assumptions. The method is tested on a phantom image, then applied to normal and Alzheimer's brains, and finally compared with another classic brain tissue segmentation method, affording a relevant classification of voxels into the different tissue classes.

Adult↗

PubMed2004

Knowledge acquisition in the fuzzy knowledge representation framework of a medical consultation system.

This paper describes the fuzzy knowledge representation framework of the medical computer consultation system MedFrame/CADIAG-IV as well as the specific knowledge acquisition techniques that have been developed to support the definition of knowledge concepts and inference rules. As in its predecessor system CADIAG-II, fuzzy medical knowledge bases are used to model the uncertainty and the vagueness of medical concepts and fuzzy logic reasoning mechanisms provide the basic inference processes. The elicitation and acquisition of medical knowledge from domain experts has often been described as the most difficult and time-consuming task in knowledge-based system development in medicine. It comes as no surprise that this is even more so when unfamiliar representations like fuzzy membership functions are to be acquired. From previous projects we have learned that a user-centered approach is mandatory in complex and ill-defined knowledge domains such as internal medicine. This paper describes the knowledge acquisition framework that has been developed in order to make easier and more accessible the three main tasks of: (a) defining medical concepts; (b) providing appropriate interpretations for patient data; and (c) constructing inferential knowledge in a fuzzy knowledge representation framework. Special emphasis is laid on the motivations for some system design and data modeling decisions. The theoretical framework has been implemented in a software package, the Knowledge Base Builder Toolkit. The conception and the design of this system reflect the need for a user-centered, intuitive, and easy-to-handle tool. First results gained from pilot studies have shown that our approach can be successfully implemented in the context of a complex fuzzy theoretical framework. As a result, this critical aspect of knowledge-based system development can be accomplished more easily.

Decision Making↗

PubMed1991

The doctor as double agent: information asymmetry, health insurance, and medical care.

In a model incorporating uncertainty and state-dependent utility of health services, as well as information asymmetry between patients/buyers and physicians/sellers, two types of equilibria are compared: (1) when consumers have conventional third-party insurance and doctors are paid on the basis of fee-for-service; and (2) when insurance is through an HMO which provides health services through its own doctors. Conditions are found under which contractual or legal incentives can overcome the information asymmetry problem and bring about an efficient allocation of resources to health services provision.

Canada↗

PubMedDate not supplied

Certainty factor theory and its implementation in a medical expert system shell.

In this article some topics related to the MYCIN-model for uncertainty handling are discussed. First, it is pointed out that one of the problems identified by Adams should be considered as evidence supporting the point of view that the probabilistic interpretations of measures of belief and measures of disbelief given by Shortliffe are inappropriate. In this context some results achieved by Heckerman are reviewed, and it is shown that similar problems can be identified in the interpretation given by him. It is also pointed out that Heckerman's argument that the original probabilistic interpretation of certainty factors implies non-commutative evidence-updating is not correct. Then, in the context of the result achieved by Horvitz and Heckerman, in which it was proven that there is an isomorphic mapping from the evidence combination scheme for the likelihood ratio to the evidence combination function in EMYCIN and its successors, it is pointed out that the evidence combination scheme for the likelihood ratio suffers from a great restriction on its applicability in expert systems. Subsequently, some short remarks are made with respect to the complaint that sometimes the MYCIN model cannot work as well as expected. Lastly implementation of the certainty factor mechanism in a HIS-oriented expert system shell with some substantial changes is described.

Databases, Factual↗

PubMed2004

Phylogenetic relationships and biogeography of the desert plant genus Fagonia (Zygophyllaceae), inferred by parsimony and Bayesian model averaging.

Phylogenetic relationships within Fagonia were inferred from analyses of plastid trnL intron and nuclear ribosomal ITS DNA sequences. Sampling of the genus was nearly complete, including 32 of 34 species. Phylogenetic analysis was carried out using parsimony, and Bayesian model averaging. The latter method allows model-based inference while accounting for model-selection uncertainty, and is here used for the first time in phylogenetic analyses. All species of Fagonia in the Old World, except F. cretica, form a weakly supported clade, and all Fagonia species of the New World, except F. scoparia, are well supported as sister to the Old World clade. Fagonia scoparia, from Mexico, and F. cretica, from Northern Africa, are well supported as sisters to all other Fagonia species. Vicariance-dispersal analysis, using DIVA, indicated that the occurrences of Fagonia in South America and southern Africa are due to dispersals, and also, that the ancestor of Fagonia had a distribution compatible with the boreotropics hypothesis.

Base Sequence↗

PubMed2001

Proposed occupational exposure limits for select ethylene glycol ethers using PBPK models and Monte Carlo simulations.

Methoxyethanol (ethylene glycol monomethyl ether, EGME), ethoxyethanol (ethylene glycol monoethyl ether, EGEE), and ethoxyethyl acetate (ethylene glycol monoethyl ether acetate, EGEEA) are all developmental toxicants in laboratory animals. Due to the imprecise nature of the exposure data in epidemiology studies of these chemicals, we relied on human and animal pharmacokinetic data, as well as animal toxicity data, to derive 3 occupational exposure limits (OELs). Physiologically based pharmacokinetic (PBPK) models for EGME, EGEE, and EGEEA in pregnant rats and humans have been developed (M. L. Gargas et al., 2000, Toxicol. Appl. Pharmacol. 165, 53-62; M. L. Gargas et al., 2000, Toxicol. Appl. Pharmacol. 165, 63-73). These models were used to calculate estimated human-equivalent no adverse effect levels (NAELs), based upon internal concentrations in rats exposed to no observed effect levels (NOELs) for developmental toxicity. Estimated NAEL values of 25 ppm for EGEEA and EGEE and 12 ppm for EGME were derived using average values for physiological, thermodynamic, and metabolic parameters in the PBPK model. The uncertainties in the point estimates for the NOELs and NAELs were estimated from the distribution of internal dose estimates obtained by varying key parameter values over expected ranges and probability distributions. Key parameters were identified through sensitivity analysis. Distributions of the values of these parameters were sampled using Monte Carlo techniques and appropriate dose metrics calculated for 1600 parameter sets. The 95th percentile values were used to calculate interindividual pharmacokinetic uncertainty factors (UFs) to account for variability among humans (UF(h,pk)). These values of 1.8 for EGEEA/EGEE and 1.7 for EGME are less than the default value of 3 for this area of uncertainty. The estimated human equivalent NAELs were divided by UF(h,pk) and the default UFs for pharmacodynamic variability among animals and among humans to calculate the proposed OELs. This methodology indicates that OELs (8-h time-weighted average) that should protect workers from the most sensitive adverse effects of these chemicals are 2 ppm EGEEA and EGEE (11 mg/m(3) EGEEA, 7 mg/m(3) EGEE) and 0.9 ppm (3 mg/m(3)) EGME. These recommendations assume that dermal exposure will be minimal or nonexistent.

Administration, Inhalation↗

PubMed1999

Propagating distributions up directed acyclic graphs.

In a previous article, we considered game trees as graphical models. Adopting an evaluation function that returned a probability distribution over values likely to be taken at a given position, we described how to build a model of uncertainty and use it for utility-directed growth of the search tree and for deciding on a move after search was completed. In some games, such as chess and Othello, the same position can occur more than once, collapsing the game tree to a directed acyclic graph (DAG). This induces correlations among the distributions at sibling nodes. This article discusses some issues that arise in extending our algorithms to a DAG. We give a simply described algorithm for correctly propagating distributions up a game DAG, taking account of dependencies induced by the DAG structure. This algorithm is exponential time in the worst case. We prove that it is #P complete to propagate distributions up a game DAG correctly. We suggest how our exact propagation algorithm can yield a fast but inexact heuristic.

Algorithms↗

PubMed2004

Use of disability adjusted life years in the estimation of the disease burden of echinococcosis for a high endemic region of the Tibetan plateau.

Shiqu County, located on the Tibetan plateau of western China, has an extremely high prevalence of both human alveolar echinococcosis (AE), and cystic echinococcosis (CE). The short form 12 version 2 quality of life survey, which was used to evaluate the extent to which morbidity associated with echinococcosis should be accounted, verified that there was a significant reduction in the mean health scores in all categories for individuals diagnosed with abdominal echinococcosis compared with an age and sex cross-matched population. Results of a larger ultrasound survey, which screened 3135 subjects, demonstrated that the prevalence rates of AE and CE were both approximately 6% with a combined prevalence rate of 11.4%. Prevalence rates adjusted for the age and sex structure of Shiqu County were 4.6% for AE and 4.9% for CE with an estimated overall adjusted prevalence rate of 9.5%. The burden of disease associated with echinococcosis was calculated using disability adjusted life years (DALYs) based on these estimated prevalence rates. Monte-Carlo techniques were used to model the uncertainty in the prevalence estimates and the disability weights. Using these methods, we estimated that the total numbers of DALYs lost due echinococcosis was 50,933 (95% confidence interval [CI] = 41,995-61,026). The DALYs lost consisted of approximately 32,978 (95% CI = 25,019-42,422) due to AE and 17,955 (95% CI = 14,268-22,128) due to CE and suggests an average of approximately 0.81 DALY lost per person. This study has clearly shown that the impact of DALYs lost due to echinococcosis, in terms of medical treatment costs, lost income, and physical and social suffering, is likely to be substantial in this highly endemic region of China.

Adolescent↗

PubMed2005

MUD: a Model to investigate the migration of 137Cs in the Urban environment and Drainage and sewage treatment systems.

A model is presented for the migration of 137Cs in the urban environment, including the drainage systems and the sewage treatment plants, with flexibility to be adapted to different configurations common in urban areas. The dynamics of 137Cs is simulated both under natural evolution and in case of forced decontamination, which can have a direct impact on the radioactivity going to sewers. The model assesses the activity concentrated in sewage sludge and that discharged with the treated or untreated effluent to the receiving watercourse. Tests made for two post-Chernobyl contamination scenarios in Sweden show differences between model predictions and observed results within the range of the experimental uncertainties. An uncertainty and sensitivity analysis of the main model parameters indicates that some parameters may have a significant influence on the results of the model. Moreover, the model uncertainty is driven by a few parameters; therefore, additional research could be necessary into these parameters, aiming at simplifying the model without losing its predictive power.

Cesium Radioisotopes↗

PubMed1998

Accidents and Decision Making under Uncertainty: A Comparison of Four Models.

Heinrich's (1931) classical study implies that most industrial accidents can be characterized as a probabilistic result of human error. The present research quantifies Heinrich's observation and compares four descriptive models of decision making in the abstracted setting. The suggested quantification utilizes signal detection theory (Green & Swets, 1966). It shows that Heinrich's observation can be described as a probabilistic signal detection task. In a controlled experiment, 90 decision makers participated in 600 trials of six safety games. Each safety game was a numerical example of the probabilistic SDT abstraction of Heinrich's proposition. Three games were designed under a frame of gain to represent perception of safe choice as costless, while the other three were designed under a frame of loss to represent perception of safe choice as costly. Probabilistic penalty for Miss was given at three different levels (1, .5, .1). The results showed that decisions tended initially to be risky and that experience led to safer behavior. As the probability of being penalized was lowered decisions became riskier and the learning process was impaired. The results support the cutoff reinforcement learning model suggested by Erev et al. (1995). The hill-climbing learning model (Busemeyer & Myung, 1992) was partially supported. Theoretical and practical implications are discussed. Copyright 1998 Academic Press.

Journal Article↗

PubMed2000

Nonlinear determination of Michaelis-Menten kinetics with model evaluation through estimation of uncertainties.

A structured analytic approach was developed to evaluate enzyme kinetic parameters using non-linear least-squares fitting. The approach was implemented in a software package called KinSim and designed to run on Windows 95, 98, and NT platforms. The software and the theoretical approach were tested using kinetic data obtained using citrate synthase with acetyl CoA as a substrate and octanoyl CoA as an inhibitor. Using the software, the data were evaluated for statistical certainty of the presence of competitive and non-competitive inhibition of the enzyme. Given the determination of the presence of both components of inhibition in the experimental setup, the software was used to determine the inhibitory kinetics from the experimental data, including non-normal distributions of uncertainty. Finally, the software was used to evaluate the sensitivities of the experiment design at each concentration of substrate used. The theoretical approach as implemented in the user-friendly software allows investigators to use a structured procedure for evaluating and planning enzyme kinetic and related metabolic studies.

Acetyl Coenzyme A↗

PubMed2000

Evaluating and Managing Cumulative Effects: Process and Constraints.

/ Cumulative effects (CEs) result from the combined effect of multiple activities over space or time. This implies a persistence through time and often a transmittal mechanism through space. Environmental legislation often requires a broader CE assessment in addition to the more direct, project-specific impacts. Current efforts to evaluate and manage CEs are hampered by the conceptual problems of defining the key issues, specifying the appropriate spatial and temporal scales, and determining the numerous interactions and indirect effects. These problems can be greatly alleviated by following an explicit process. The process proposed in this paper includes a scoping phase, an analysis phase, and a planning and management phase, with each phase consisting of two to five discrete but interrelated tasks. Numerous approaches have been developed to assess CEs, and these range from simple checklists to complex, physically based models. The utility of each approach depends on the resource of concern, relative risk to those resources, information available, and time frame for the evaluation. In nearly all cases the assessment and regulation of CEs is severely hampered by the variability in site conditions and management effects, inability to predict secondary or indirect effects, lack of data on recovery rates, difficulty of validating predictive models, and uncertainty of future events.Since any proposed activity could contribute to a wide range of potential CEs at different spatial and temporal scales, a tiered or nested approach should be followed to assess CEs. The difficulty of assessing and predicting CEs also suggests that in many cases the most efficient approach is to focus on minimizing on-site impacts. Under some circumstances adaptive management can also be a viable alternative to detailed CE assessments. Regular monitoring and feedback is critical to the successful management and regulation of CEs.

Journal Article↗

PubMed2004

Conflicting phylogenies of balsaminoid families and the polytomy in Ericales: combining data in a Bayesian framework.

The balsaminoid Ericales, namely Balsaminaceae, Marcgraviaceae, Tetrameristaceae, and Pellicieraceae have been confidently placed at the base of Ericales, but the relations among these families have been resolved differently in recent analyses. Sister to this basal group is a large polytomy comprising all other families of Ericales, which is associated with short internodes. Because there are more than 13 kb of sequences for a large sampling of representatives, a thorough examination of the available data with novel methods seemed in place. Because of its computational speed, Bayesian phylogenetics allows for the use of parameter-rich models that can accommodate differences in the evolutionary process between partitions in a simultaneous analysis. In addition, there are recently proposed Bayesian strategies of assessing incongruence between partitions. We have applied these methods to the current problems in Ericales phylogeny, taking into account reported pitfalls in Bayesian analysis such as model selection uncertainty. Based on our results we infer several, previously unresolved relationships in the order Ericales. In balsaminoid families, we find that the closest relatives of Balsaminaceae are Marcgraviaceae. In the Ericales polytomy, we find strong support for Pentaphylacaceae sensu APG II as the sister group of Maesaceae. In addition, Symplocaceae receive a position as sister to Theaceae and these families form a monophyletic group together with Styracaceae-Diapensiaceae. At the base of this clade are Actinidiaceae and Clethraceae. The positions of Ebenaceae and Lecythidaceae remain uncertain.

Balsaminaceae↗

PubMed1999

Consumer information and competition between nonprofit and for-profit nursing homes.

This paper develops implications of Arrow's hypothesis that nonprofit organizations are prevalent in health care because of quality uncertainty. The model analyzes the ability of nonprofits to mitigate market failures created by asymmetric information in an environment characterized by potential competition from both explicitly for-profit firms and for-profits in disguise (profit-motivated firms who obtain nonprofit status in order to exploit the perceived trustworthiness of the nonprofit sector). Under certain conditions, it is shown that nonprofit status can serve as a credible signal of quality and that nonprofits can decrease the underprovision of quality both by providing high quality services and indirectly via a spillover effect on quality in the for-profit sector. Applicability to long-term care and implications for empirical research and policy towards nonprofits in health care are discussed.

Benchmarking↗

PubMed2006

Comparative study of parameter sensitivity analyses of the TCR-activated Erk-MAPK signalling pathway.

Parameter estimation is a major challenge for mathematical modelling of biological systems. Given the uncertainties associated with model parameters, it is important to understand how sensitive the model output is to variations in parameter values. A local sensitivity analysis determines the model sensitivity to parameter variations over a localised region around the nominal parameter values, whereas a global sensitivity analysis (GSA) investigates the sensitivity over the entire parameter space. Using a T-cell receptor-activated Erk-MAPK signalling pathway model as an example, the authors present a comparative study of a variety of different sensitivity analysis techniques. These techniques include: local sensitivity analysis, existing GSA methods of partial rank correlation coefficient, Sobol's, extended Fourier amplitude sensitivity test, as well as a weighted average of local sensitivities and a new GSA method to extract global parameter sensitivities from a parameter identification routine. Results of this study revealed critical reactions in the signalling pathway and their impact on the signalling dynamics and provided insights into embedded regulatory mechanisms such as feedback loops in the pathway. From this study, a recommendation emerges for a general sensitivity analysis strategy to efficiently and reliably infer quantitative, dynamic as well as topological properties from systems biology models.

Algorithms↗

PubMed1997

Monte Carlo uncertainty analysis of a diffusion model for the assessment of halogen gas exposure during dosing of brominators.

Monte Carlo simulation was incorporated into a diffusion-based exposure assessment model for the estimation of worker exposure to halogen gases during dosing of 500-lb sacks of a bromine-based biocide (BCDMH) into brominators. Indoor and outdoor dosing scenarios were modeled for small and large brominators. The diffusion model used describes a concentration gradient of halogen as a function of distance and time from the source instead of ascribing worst-case single point value estimates to the variables used in the diffusion model. Monte Carlo simulation was used to describe a distribution of values for each appropriate model variable. Using a personal computer and Monte Carlo simulation software, 10,000 iterations of the diffusion model were performed for four different dosing scenarios using random and independent samples from the distributions entered. The corresponding output distributions of predicted exposures were then calculated and displayed graphically for each scenario. The results of the Monte Carlo simulation predict that outdoor dosing of either small or large brominators with BCDMH is highly unlikely to result in an exceedance of the working occupational exposure limit for total halogen. In most ambient wind speed conditions, diffusion prevents appreciable airborne exposure to workers in the immediate vicinity of the brominator. Although relatively uncommon, dosing of brominators indoors in the assumed absence of local exhaust ventilation may generate airborne concentrations of total halogen that exceed the working short-term occupational exposure limit. Although very limited and inconclusive, field trial monitoring of BCDMH transfer operations indoors resulted in halogen concentrations well within the distribution of concentrations predicted by the Monte Carlo simulation of the diffusion model.

Air Pollution↗

PubMed2000

Power comparison of parametric and nonparametric linkage tests in small pedigrees.

When the mode of inheritance of a disease is unknown, the LOD-score method of linkage analysis must take into account uncertainties in model parameters. We have previously proposed a parametric linkage test called "MFLOD," which does not require specification of disease model parameters. In the present study, we introduce two new model-free parametric linkage tests, known as "MLOD" and "MALOD." These tests are defined, respectively, as the LOD score and the admixture LOD score, maximized (subject to the same constraints as MFLOD) over disease-model parameters. We compared the power of these three parametric linkage tests and that of two nonparametric linkage tests, NPLall and NPLpairs, which are implemented in GENEHUNTER. With the use of small pedigrees and a fully informative marker, we found the powers of MLOD, NPLall, and NPLpairs to be almost equivalent to each other and not far below that of a LOD-score analysis performed under the assumption the correct genetic parameters. Thus, linkage analysis is not much hindered by uncertain mode of inheritance. The results also suggest that both parametric and nonparametric methods are suitable for linkage analysis of complex disorders in small pedigrees. However, whether these results apply to large pedigrees remains to be answered.

Chromosome Mapping↗

PubMed1994

The international normalized ratio and uncertainty. Validation of a probabilistic model.

The motivation behind the creation of the International Normalized Ratio (INR) was to improve interlaboratory comparison for patients on anticoagulation therapy. In principle, a laboratory that reports the prothrombin time (PT) as an INR can standardize its PT measurements to an international reference thromboplastin. Using probability theory, the authors derived the equation for the probability distribution of the INR based on the PT, the International Sensitivity Index (ISI), and the geometric mean PT of the reference population. With Monte Carlo and numeric integration techniques, the model is validated on data from three different laboratories. The model allows computation of confidence intervals for the INR as a function of PT, ISI, and reference mean. The probabilistic model illustrates that confidence in INR measurements degrades for higher INR values. This occurs primarily as a result of amplification of between-run measurement errors in the PT, which is inherent in the mathematical transformation from the PT to the INR. The probabilistic model can be used by any laboratory to study the reliability of its own INR for any measured PT. This framework provides better insight into the problems of monitoring oral anticoagulation.

Evaluation Studies as Topic↗