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PubMed1998

Refractoriness and neural precision.

The response of a spiking neuron to a stimulus is often characterized by its time-varying firing rate, estimated from a histogram of spike times. If the cell's firing probability in each small time interval depends only on this firing rate, one predicts a highly variable response to repeated trials, whereas many neurons show much greater fidelity. Furthermore, the neuronal membrane is refractory immediately after a spike, so that the firing probability depends not only on the stimulus but also on the preceding spike train. To connect these observations, we investigated the relationship between the refractory period of a neuron and its firing precision. The light response of retinal ganglion cells was modeled as probabilistic firing combined with a refractory period: the instantaneous firing rate is the product of a "free firing rate, " which depends only on the stimulus, and a "recovery function," which depends only on the time since the last spike. This recovery function vanishes for an absolute refractory period and then gradually increases to unity. In simulations, longer refractory periods were found to make the response more reproducible, eventually matching the precision of measured spike trains. Refractoriness, although often thought to limit the performance of neurons, may in fact benefit neuronal reliability. The underlying free firing rate derived by allowing for the refractory period often exceeded the observed firing rate by an order of magnitude and was found to convey information about the stimulus over a much wider dynamic range. Thus, the free firing rate may be the preferred variable for describing the response of a spiking neuron.

Action Potentials↗
PubMed2005

Cost-effectiveness of endovascular abdominal aortic aneurysm repair.

BACKGROUND: The rapid introduction of endovascular abdominal aortic aneurysm repair (EVAR) has considerable implications for the management of abdominal aortic aneurysm (AAA). This study was undertaken to determine an optimal strategy for the use of EVAR based on the best currently available evidence. METHODS: Economic modelling and probabilistic sensitivity analysis considered reference cases representing a fit 70-year-old with a 5.5-cm diameter AAA (RC1) and an 80-year-old with a 6.5-cm AAA unfit for open surgery (RC2). Results were assessed as incremental cost-effectiveness ratio (ICER) compared with open repair (RC1) or conservative management (RC2). RESULTS: In RC1 EVAR produced a gain of 0.10 quality-adjusted life years (QALYs) for an estimated cost of 11,449 pound, giving an ICER of 110,000 pound per QALY. EVAR consistently had an ICER above 30,000 pound per QALY over a range of sensitivity analyses and alternative scenarios. In RC2 EVAR produced an estimated benefit of 1.64 QALYs for an incremental cost of 14,077 pound giving an incremental cost per QALY of 8579 pound. CONCLUSION: : It is unlikely that EVAR for fit patients suitable for open repair is within the commonly accepted range of cost-effectiveness for a new technology. For those unfit for conventional open repair it is likely to be a cost-effective alternative to non-operative management. Sensitivity analysis suggests that research efforts should concentrate on determining accurate rates for late complications and reintervention, particularly in patients with high operative risks.

Aged↗
PubMed1985

A statistical reevaluation of the STAI anxiety questionnaire.

This study examined the capability and efficiency of two commonly used scales, the trait and trait and state inventories (Spielberger et al., 1970), to measure anxiety construct (N = 100). The probabilistic Rasch Model (Wright & Masters, 1982) was applied to athletes' responses to trait and state anxiety items before competition (stress). The analysis indicated that several items of both scales produce misfit responses, share identical locations on the continuum, and do not produce equal units of measurement. The findings question the generalizability of the research on anxiety. Recommendations for improving the anxiety tests are made.

Adult↗
PubMed1994

A cost-utility analysis of misoprostol prophylaxis for rheumatoid arthritis patients receiving nonsteroidal antiinflammatory drugs.

OBJECTIVE: To determine the cost-utility of low-dose misoprostol prophylaxis in rheumatoid arthritis (RA) patients treated with nonsteroidal antiinflammatory drugs (NSAIDs). METHODS: Prospectively collected, population-based data on 57 RA patients' preferences (obtained using the category scaling and time trade-off techniques), charge data from a consecutive, population-based cohort of 36 RA patients with NSAID-related gastric ulcer, and literature-derived probability estimates were incorporated into a decision analysis model. RESULTS: Probabilistic sensitivity analysis using 10,000 Monte Carlo simulations demonstrated that, on average, prophylaxis resulted in modest additional costs and no additional quality-of-life benefits. At best, the incremental cost per quality-adjusted life year gained was $9,333. At worst, prophylaxis reduced quality of life. Prophylaxis was cost-saving if the ulcer complication rate was > 1.5%, or if the 3-month price of misoprostol was < or = $95. CONCLUSION: Whereas prophylaxis may be cost-saving among high-risk NSAID users, from some patients' perspective, it reduces quality of life. Although these data may not be generalizable to other clinical populations, they illustrate the importance of incorporating patient preferences into economic evaluations.

Adult↗
PubMed2000

A measure of sexual dimorphism in populations which are univariate normal mixtures.

Measures of sexual dimorphism have been used extensively to predict the social organization and ecology of animal and human populations. There is, however, no universally accepted measure of phenotypic differences between the sexes. Most indices of sexual dimorphism fail to incorporate all of the information contained in a random data set. In an attempt to have a better alternative, an index is proposed to measure sexual dimorphism in populations that are distributed according to a probabilistic mixture model with two normal components. The index calculates the overlap between two functions that represent the contribution of each sex in the mixture. In order to assess such an index, sample means, variances and sizes of each sex are needed. As a consequence, the sample information used is greater than that used by other indices that take intrasexual variability into account. By evaluating some examples, our proposed index appears to be a more realistic measure of sexual dimorphism than other measures currently used.

Animals↗
PubMed2001

Random Trajectory Modeling of Limited-Volume Percolation in a Microporous Structure.

The limited-volume analytical method for the evaluation of the probability of percolation (random trajectory approach) is developed. The model uses probabilistic analysis of possible percolation ways. The main equation for the probability of percolation contains parameters related to the conditions of formation of the microporous medium. Results of some computer estimations of the influence of various formation-related parameters (porosity, surface tension, coordination number, etc.) are presented. Copyright 2001 Academic Press.

Journal Article↗
PubMed1994

Ab-Ag affinity thresholds in inventory optimization.

The role of antibody-antigen affinity and concentrations in adaptive antibody response is analyzed in a framework of probabilistic inventory model for antibody production. Our results indicate significant differences in optimal behaviours of low, moderate and high affinity groups and offer important implications. Interestingly, the involved approach is also of relevance in other production systems. Directions for its applications in industries and information sciences are also presented.

Animals↗
PubMed2006

Cost-effectiveness of the Danish smoking cessation interventions: subgroup analysis based on the Danish Smoking Cessation Database.

The cost-effectiveness of smoking cessation interventions is well documented. However, most studies are based on randomized controlled trials (RCTs) and provide little information on the differences between subgroups. This study assessed the relative cost-effectiveness of smoking cessation interventions offered to various subgroups of smokers, based on real-life data. Regression analyses provided information on the factors determining abstinence and costs and led to the formation of relevant subgroups of smokers. Probabilistic Markov modeling was then used to estimate the relative cost-effectiveness of smoking cessation interventions for the entire database population and for the subgroups compared to a no-intervention case. The ICER for the base case population was estimated at 1,358 euro. This is consistent with results from the existing literature. Group simulations showed lower ICERs for men, hospitals, and light smokers and falling ICERs with increasing age. Despite differences in the cost-effectiveness ratios between subgroups our results do not justify any kind of subgroup differentiation in a smoking prevention policy.

Adolescent↗
PubMed1987

Decisions relating to alcohol-impaired driving: an exploratory analysis.

This paper focuses on an individual's decision to drive or not to drive after drinking. To evaluate this decision, a utility maximizing probabilistic choice model is specified and estimated using a sample of college students. The estimation results provide interesting insights relating to the potential effectiveness of drinking-driving countermeasures, and suggest that the most effective methods of reducing the probability of driving after drinking are those advertising and awareness campaigns that focus on altering individual preferences.

Adult↗
PubMed1996

Reduced perceptual dimensionality in extrafoveal vision.

The classification behaviour of human observers with respect to compound Gabor signals is tested at foveal and extrafoveal retinal positions. Classification performance is analysed in terms of a probabilistic classification model recently proposed by Rentschler, Jüttner and Caelli [(1994) Vision Research, 34, 669-687]. The analysis allows inferences about structure and dimensionality of the individual internal representations underlying the classification task and their temporal evolution during the learning process. Using this technique it is found that the internal representations of direct and eccentric viewing are intrinsically incommensurable, in the sense that extrafoveal pattern representations are characterized by a lower perceptual dimension in feature space relative to the corresponding physical input signals, whereas foveal representations are not. The observed deficits cannot be renormalized by size scaling (cortical magnification); however, they can be partially reduced by learning although the learning progress strongly depends on the observer's practice. The structural incommensurability between foveal and extrafoveal representations poses constraints on possible forms of foveal-extrafoveal interaction, which might have implications on related perceptual phenomena such as visual stability across saccadic eye movements.

Adult↗
PubMed1993

The use of statistical methods in the analysis of clinical studies.

It is "standard" to analyze data from a clinical trial using a narrowly defined probabilistic mathematical model. This paper examines the ways in which mathematical models, in general, can be used in clinical research, the meaning of probability in the examination of clinical trials, and the philosophical flaws in the current "standard" method. An alternative formulation is proposed which is more flexible and which comes closer to meeting the needs of medical science. In this alternative formulation, significance tests are applied to the data from a study only as a first step to determine whether the data are worth further examination. After that, clinically relevant questions are answered with 50 and 95% confidence bounds. The initial significance test is tailored to be directed at a narrow class of hypotheses that, in turn, are dictated by clinical expectations.

Clinical Trials as Topic↗
PubMed1995

A theoretical approach to artificial intelligence systems in medicine.

The various theoretical models of disease, the nosology which is accepted by the medical community and the prevalent logic of diagnosis determine both the medical approach as well as the development of the relevant technology including the structure and function of the A.I. systems involved. A.I. systems in medicine, in addition to the specific parameters which enable them to reach a diagnostic and/or therapeutic proposal, entail implicitly theoretical assumptions and socio-cultural attitudes which prejudice the orientation and the final outcome of the procedure. The various models -causal, probabilistic, case-based etc. -are critically examined and their ethical and methodological limitations are brought to light. The lack of a self-consistent theoretical framework in medicine, the multi-faceted character of the human organism as well as the non-explicit nature of the theoretical assumptions involved in A.I. systems restrict them to the role of decision supporting "instruments" rather than regarding them as decision making "devices". This supporting role and, especially, the important function which A.I. systems should have in the structure, the methods and the content of medical education underscore the need of further research in the theoretical aspects and the actual development of such systems.

Artificial Intelligence↗
PubMed2006

Modeling motor vehicle crashes using Poisson-gamma models: examining the effects of low sample mean values and small sample size on the estimation of the fixed dispersion parameter.

There has been considerable research conducted on the development of statistical models for predicting crashes on highway facilities. Despite numerous advancements made for improving the estimation tools of statistical models, the most common probabilistic structure used for modeling motor vehicle crashes remains the traditional Poisson and Poisson-gamma (or Negative Binomial) distribution; when crash data exhibit over-dispersion, the Poisson-gamma model is usually the model of choice most favored by transportation safety modelers. Crash data collected for safety studies often have the unusual attributes of being characterized by low sample mean values. Studies have shown that the goodness-of-fit of statistical models produced from such datasets can be significantly affected. This issue has been defined as the "low mean problem" (LMP). Despite recent developments on methods to circumvent the LMP and test the goodness-of-fit of models developed using such datasets, no work has so far examined how the LMP affects the fixed dispersion parameter of Poisson-gamma models used for modeling motor vehicle crashes. The dispersion parameter plays an important role in many types of safety studies and should, therefore, be reliably estimated. The primary objective of this research project was to verify whether the LMP affects the estimation of the dispersion parameter and, if it is, to determine the magnitude of the problem. The secondary objective consisted of determining the effects of an unreliably estimated dispersion parameter on common analyses performed in highway safety studies. To accomplish the objectives of the study, a series of Poisson-gamma distributions were simulated using different values describing the mean, the dispersion parameter, and the sample size. Three estimators commonly used by transportation safety modelers for estimating the dispersion parameter of Poisson-gamma models were evaluated: the method of moments, the weighted regression, and the maximum likelihood method. In an attempt to complement the outcome of the simulation study, Poisson-gamma models were fitted to crash data collected in Toronto, Ont. characterized by a low sample mean and small sample size. The study shows that a low sample mean combined with a small sample size can seriously affect the estimation of the dispersion parameter, no matter which estimator is used within the estimation process. The probability the dispersion parameter becomes unreliably estimated increases significantly as the sample mean and sample size decrease. Consequently, the results show that an unreliably estimated dispersion parameter can significantly undermine empirical Bayes (EB) estimates as well as the estimation of confidence intervals for the gamma mean and predicted response. The paper ends with recommendations about minimizing the likelihood of producing Poisson-gamma models with an unreliable dispersion parameter for modeling motor vehicle crashes.

Accidents, Traffic↗
PubMed2025

Leveraging functional annotations to map rare variants associated with Alzheimer disease with gruyere.

Increased availability of whole-genome sequencing (WGS) has facilitated the study of rare variants (RVs) in complex diseases. Multiple RV association tests are available to study the relationship between genotype and phenotype, but most do not fully leverage the availability of variant-level functional annotations. We propose genome-wide rare variant enrichment evaluation (gruyere), an empirical Bayesian framework that complements existing methods by learning global, trait-specific weights for functional annotations to improve variant prioritization. We apply gruyere to WGS data from the Alzheimer's Disease Sequencing Project to identify Alzheimer disease (AD)-associated genes and annotations. Growing evidence suggests that the disruption of microglial regulation is a key contributor to AD risk, yet existing methods have not examined rare non-coding effects that incorporate such cell-type-specific information. To address this gap, we (1) define per-gene non-coding RV test sets using predicted enhancer and promoter regions in microglia and other brain cell types (oligodendrocytes, astrocytes, and neurons) and (2) include cell-type-specific variant effect predictions (VEPs) as functional annotations. gruyere identifies 13 significant genetic associations not detected by other RV methods, four of which remain significant in omnibus tests. We find that deep-learning-based VEPs for splicing, transcription factor binding, and chromatin state are highly predictive of functional non-coding RVs. Our study establishes a robust framework incorporating functional annotations, coding RVs, and cell-type-associated non-coding RVs to perform genome-wide association tests, uncovering AD-relevant genes and annotations.

Alzheimer Disease↗
PubMed2005

A cost-effectiveness analysis of fluvastatin in patients with diabetes after successful percutaneous coronary intervention.

BACKGROUND: The Lescol Intervention Prevention Study (LIPS) was a multinational randomized controlled trial that showed a 47% reduction in the relative risk of cardiac death and a 22% reduction in major adverse cardiac events (MACEs) from the routine use of fluvastatin, compared with controls, in patients undergoing percutaneous coronary intervention (PCI, defined as angioplasty with or without stents). In this study, MACEs included cardiac death, nonfatal myocardial infarction, and subsequent PCI and coronary artery bypass graft. Diabetes was the greatest risk factor for MACEs. OBJECTIVE: This study estimated the cost-effectiveness of fluvastatin when used for secondary prevention of MACEs after PCI in people with diabetes. METHODS: A post hoc subgroup analysis of patients with diabetes from the LIPS was used to estimate the effectiveness of fluvastatin in reducing myocardial infarction, revascularization, and cardiac death. A probabilistic Markov model was developed using United Kingdom resource and cost data to estimate the additional costs and quality-adjusted life-years (QALYs) gained over 10 years from the perspective of the British National Health Service. The model contained 6 health states, and the transition probabilities were derived from the LIPS data. Crossover from fluvastatin to other lipid-lowering drugs, withdrawal from fluvastatin, and the use of lipid-lowering drugs in the control group were included. RESULTS: In the subgroup of 202 patients with diabetes in the LIPS trial, 18 (15.0%) of 120 fluastatin patients and 21 (25.6%) of 82 control participants were insulin dependent (P = NS). Compared with the control group, patients treated with fluvastatin can expect to gain an additional mean (SD) of 0.196 (0.139) QALY per patient over 10 years (P < 0.001) and will cost the health service an additional mean (SD) of 10 pounds ( 448 pounds) (P = NS) (mean [SD] US $16 [$689]). The additional cost per QALY gained was 51 pounds (US $78). The key determinants of cost-effectiveness included the probabilities of repeat interventions, cardiac death, the cost of fluvastatin, and the time horizon used for the evaluation. CONCLUSION: Fluvastatin was an economically efficient treatment to prevent MACEs in these patients with diabetes undergoing PCI.

Angioplasty, Balloon, Coronary↗
PubMed2006

Segmentation of kidney from ultrasound B-mode images with texture-based classification.

The segmentation of anatomical structures from sonograms can help physicians evaluate organ morphology and realize quantitative measurement. It is an important but difficult issue in medical image analysis. In this paper, we propose a new method based on Laws' microtexture energies and maximum a posteriori (MAP) estimation to construct a probabilistic deformable model for kidney segmentation. First, using texture image features and MAP estimation, we classify each image pixel as inside or outside the boundary. Then, we design a deformable model to locate the actual boundary and maintain the smooth nature of the organ. Using gradient information subject to a smoothness constraint, the optimal contour is obtained by the dynamic programming technique. Experiments on different datasets are described. We find this method to be an effective approach.

Humans↗
PubMed2006

Assessment of the impact of cattle testing strategies on human exposure to BSE agents in Japan.

In Japan, cattle screening tests for BSE are conducted at slaughterhouses for surveillance purposes and as a meat safety measure, but the public health impacts of such testing and the subsequent removal of positive animals from the food chain have not been quantitatively assessed. We evaluated the influence of removing specified risk materials and the alternation of age limits for testing cattle at the slaughterhouse on human exposure to the BSE agent in Japan by constructing a probabilistic risk model. A stochastic model using Monte Carlo simulation was constructed in order to estimate the BSE infectivity destined for the food chain from a single BSE-infected animal at slaughter. The impact of different testing strategies and risk material removal were then compared. Murine intra-cerebral ID50 (m.i.c. ID50) units were used as units for BSE infectivity. Sensitivity analysis was conducted for key input variables by changing values within plausible ranges. The expected fraction of BSE-infected cattle presented for slaughter that would be detected by screening tests was 20%, even if all slaughtered cattle were tested. The removal of risk materials reduced the median value estimate of infectivity destined for human consumption by 95%. Cattle screening tests reduced the infectivity further, but reduction efficacy did not differ among the various testing strategies. Sensitivity analysis indicated that the characteristics of BSE infectivity accumulation during the incubation period, extension of the incubation period, and lowering the detection limit of screening tests had no significant impact on relative infectivity reduction, which remained stable irrespective of testing strategy or changes in these parameters. This study suggests that the impact of changing the age limit for testing cattle on beef safety is small, provided that the removal of risk materials is conducted properly.

Abattoirs↗
PubMed2004

Advances in risk-benefit evaluation using probabilistic simulation methods: an application to the prophylaxis of deep vein thrombosis.

OBJECTIVE: To demonstrate the use of probabilistic simulation modeling to estimate the joint density of therapeutic risks and benefits. Published data are used to introduce the risk-benefit acceptability curve as a novel method of illustrating risk-benefit analysis. STUDY DESIGN AND SETTING: Using published data, we performed a second-order Monte Carlo simulation to estimate the joint density of major bleeding and deep vein thrombosis (DVT) secondary to enoxaparin or unfractionated heparin. Within a Bayesian framework, beta-distributions for the probabilities of experiencing a DVT and major bleed were derived from the clinical trial, and incremental probabilities were calculated. RESULTS: The incremental risk-benefit pairs from 3,000 simulations are presented on a risk-benefit plane. To accommodate different risk preferences, the results are also illustrated using a risk-benefit acceptability curve, which incorporates different risk-benefit acceptability thresholds (mu), or the number of major bleeds one is willing to accept in order to avert one DVT. Finally, a net-benefit curve is used to illustrate the risk-benefit ratio and the derivation of 95% confidence intervals around the ratio. CONCLUSION: Modern simulation methods permit the estimation of the joint density of risks and benefits with their associated uncertainty, and within a Bayesian framework, facilitate the estimation of the probability that a therapy is net-beneficial over different preference thresholds for risk-benefit trade-offs.

Anticoagulants↗