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PubMed2005

Clustering ensembles: models of consensus and weak partitions.

Clustering ensembles have emerged as a powerful method for improving both the robustness as well as the stability of unsupervised classification solutions. However, finding a consensus clustering from multiple partitions is a difficult problem that can be approached from graph-based, combinatorial, or statistical perspectives. This study extends previous research on clustering ensembles in several respects. First, we introduce a unified representation for multiple clusterings and formulate the corresponding categorical clustering problem. Second, we propose a probabilistic model of consensus using a finite mixture of multinomial distributions in a space of clusterings. A combined partition is found as a solution to the corresponding maximum-likelihood problem using the EM algorithm. Third, we define a new consensus function that is related to the classical intraclass variance criterion using the generalized mutual information definition. Finally, we demonstrate the efficacy of combining partitions generated by weak clustering algorithms that use data projections and random data splits. A simple explanatory model is offered for the behavior of combinations of such weak clustering components. Combination accuracy is analyzed as a function of several parameters that control the power and resolution of component partitions as well as the number of partitions. We also analyze clustering ensembles with incomplete information and the effect of missing cluster labels on the quality of overall consensus. Experimental results demonstrate the effectiveness of the proposed methods on several real-world data sets.

Algorithms↗
PubMed2002

Analysis of uncertainty in health care cost-effectiveness studies: an introduction to statistical issues and methods.

Cost-effectiveness analysis is now an integral part of health technology assessment and addresses the question of whether a new treatment or other health care program offers good value for money. In this paper we introduce the basic framework for decision making with cost-effectiveness data and then review recent developments in statistical methods for analysis of uncertainty when cost-effectiveness estimates are based on observed data from a clinical trial. Although much research has focused on methods for calculating confidence intervals for cost-effectiveness ratios using bootstrapping or Fieller's method, these calculations can be problematic with a ratio-based statistic where numerator and/or denominator can be zero. We advocate plotting the joint density of cost and effect differences, together with cumulative density plots known as cost-effectiveness acceptability curves (CEACs) to summarize the overall value-for-money of interventions. We also outline the net-benefit formulation of the cost-effectiveness problem and show that it has particular advantages over the standard incremental cost-effectiveness ratio formulation.

Clinical Trials as Topic↗
PubMed1997

Torsional directed walks, entropic elasticity, and DNA twist stiffness.

DNA and other biopolymers differ from classical polymers because of their torsional stiffness. This property changes the statistical character of their conformations under tension from a classical random walk to a problem we call the "torsional directed walk." Motivated by a recent experiment on single lambda-DNA molecules [Strick, T. R., Allemand, J.-F., Bensimon, D., Bensimon, A. & Croquette, V. (1996) Science 271, 1835-1837], we formulate the torsional directed walk problem and solve it analytically in the appropriate force regime. Our technique affords a direct physical determination of the microscopic twist stiffness C and twist-stretch coupling D relevant for DNA functionality. The theory quantitatively fits existing experimental data for relative extension as a function of overtwist over a wide range of applied force; fitting to the experimental data yields the numerical values C = 120 nm and D = 50 nm. Future experiments will refine these values. We also predict that the phenomenon of reduction of effective twist stiffness by bend fluctuations should be testable in future single-molecule experiments, and we give its analytic form.

Animals↗
PubMed1996

Radiopharmaceutical-related pitfalls and artifacts.

The primary goal of this review article is to increase the reader's knowledge and understanding of problems associated with the radiopharmaceuticals commonly used in daily practice. To achieve this objective, problems related to the commonly used radiopharmaceuticals are divided into pitfalls and artifacts related to radiopharmaceutical preparation (technetium-99m [99mTc]-labeled and non-99mTc-labeled radiopharmaceutical) and those related to radiopharmaceutical administration. For the radiopharmaceutical formulation-associated pitfalls and artifacts, problems are discussed in terms of factor categories, such as factors associated with radionuclides, factors associated with components, factors associated with preparation procedures, and miscellaneous factors. As for the pitfalls and artifacts caused by radiopharmaceutical administration, these problems are categorized into errors associated with administration technique and nontechnical errors. Clinical manifestations (ie, appearance upon imaging) from the numerous literature-based examples are presented. The effect of the causative factors and the reason each factor can result in radiopharmaceutical preparation and administration problems are discussed. In addition, the possible preventive actions are presented for each group. However, the cause of some pharmaceutical related problems may not be easily recognized, and thus it is difficult to develop preventive and/or corrective plans for these cases.

Artifacts↗
PubMedDate not supplied

A linear semi-infinite programming strategy for constructing optimal wavelet transforms in multivariate calibration problems.

A novel strategy for the optimization of wavelet transforms with respect to the statistics of the data set in multivariate calibration problems is proposed. The optimization follows a linear semi-infinite programming formulation, which does not display local maxima problems and can be reproducibly solved with modest computational effort. After the optimization, a variable selection algorithm is employed to choose a subset of wavelet coefficients with minimal collinearity. The selection allows the building of a calibration model by direct multiple linear regression on the wavelet coefficients. In an illustrative application involving the simultaneous determination of Mn, Mo, Cr, Ni, and Fe in steel samples by ICP-AES, the proposed strategy yielded more accurate predictions than PCR, PLS, and nonoptimized wavelet regression.

Journal Article↗
PubMedDate not supplied

An investigation of numerical grid effects in parameter estimation.

Modern ground water characterization and remediation projects routinely require calibration and inverse analysis of large three-dimensional numerical models of complex hydrogeological systems. Hydrogeologic complexity can be prompted by various aquifer characteristics including complicated spatial hydrostratigraphy and aquifer recharge from infiltration through an unsaturated zone. To keep the numerical models computationally efficient, compromises are frequently made in the model development, particularly, about resolution of the computational grid and numerical representation of the governing flow equation. The compromise is required so that the model can be used in calibration, parameter estimation, performance assessment, and analysis of sensitivity and uncertainty in model predictions. However, grid properties and resolution as well as applied computational schemes can have large effects on forward-model predictions and on inverse parameter estimates. We investigate these effects for a series of one- and two-dimensional synthetic cases representing saturated and variably saturated flow problems. We show that "conformable" grids, despite neglecting terms in the numerical formulation, can lead to accurate solutions of problems with complex hydrostratigraphy. Our analysis also demonstrates that, despite slower computer run times and higher memory requirements for a given problem size, the control volume finite-element method showed an advantage over finite-difference techniques in accuracy of parameter estimation for a given grid resolution for most of the test problems.

Calibration↗
PubMed2006

[Survey on drug-related problems in Lithuania's pharmacies].

OBJECTIVE: to survey the most common and the most important drug-related problems in Lithuania, to explore their solution and factors influencing it, to formulate recommendations for solving drug-related problems. MATERIAL AND METHODS: Pharmacists from community pharmacies participated in a random survey. They filled in questionnaires about drug-related problems and their solutions. It was the first survey on drug-related problems ever carried out in Lithuania. RESULTS: For the first time, it was found out that in Lithuania pharmacists most commonly encountered drug-related problem--additional drug therapy (52.03% of respondents)--and most rarely encountered drug-related problem--dosage too high (3% of respondents). Pharmacists stated that all categories of drug-related problems were of equal importance. It was established that pharmacists commonly solved drug-related problems associated with noncompliance with instructions (72.5% of respondents) and rarely met the problem when improper drug was selected (39.56% of respondents). CONCLUSION: Patients taking prescription medicines commonly encounter additional drug therapy problem, and patients taking nonprescription medications commonly encounter problems related to noncompliance with instructions.

Community Pharmacy Services↗
PubMed2005

A theory of cortical responses.

This article concerns the nature of evoked brain responses and the principles underlying their generation. We start with the premise that the sensory brain has evolved to represent or infer the causes of changes in its sensory inputs. The problem of inference is well formulated in statistical terms. The statistical fundaments of inference may therefore afford important constraints on neuronal implementation. By formulating the original ideas of Helmholtz on perception, in terms of modern-day statistical theories, one arrives at a model of perceptual inference and learning that can explain a remarkable range of neurobiological facts.It turns out that the problems of inferring the causes of sensory input (perceptual inference) and learning the relationship between input and cause (perceptual learning) can be resolved using exactly the same principle. Specifically, both inference and learning rest on minimizing the brain's free energy, as defined in statistical physics. Furthermore, inference and learning can proceed in a biologically plausible fashion. Cortical responses can be seen as the brain's attempt to minimize the free energy induced by a stimulus and thereby encode the most likely cause of that stimulus. Similarly, learning emerges from changes in synaptic efficacy that minimize the free energy, averaged over all stimuli encountered. The underlying scheme rests on empirical Bayes and hierarchical models of how sensory input is caused. The use of hierarchical models enables the brain to construct prior expectations in a dynamic and context-sensitive fashion. This scheme provides a principled way to understand many aspects of cortical organization and responses. The aim of this article is to encompass many apparently unrelated anatomical, physiological and psychophysical attributes of the brain within a single theoretical perspective. In terms of cortical architectures, the theoretical treatment predicts that sensory cortex should be arranged hierarchically, that connections should be reciprocal and that forward and backward connections should show a functional asymmetry (forward connections are driving, whereas backward connections are both driving and modulatory). In terms of synaptic physiology, it predicts associative plasticity and, for dynamic models, spike-timing-dependent plasticity. In terms of electrophysiology, it accounts for classical and extra classical receptive field effects and long-latency or endogenous components of evoked cortical responses. It predicts the attenuation of responses encoding prediction error with perceptual learning and explains many phenomena such as repetition suppression, mismatch negativity (MMN) and the P300 in electroencephalography. In psychophysical terms, it accounts for the behavioural correlates of these physiological phenomena, for example, priming and global precedence. The final focus of this article is on perceptual learning as measured with the MMN and the implications for empirical studies of coupling among cortical areas using evoked sensory responses.

Biophysical Phenomena↗
PubMed1997

Optimal harvesting from a population in a stochastic crowded environment.

We study the (Ito) stochastic differential equation [equation: see text] as a model for population growth in a stochastic environment with finite carrying capacity K > 0. Here r and alpha are constants and Bt denotes Brownian motion. If r > or = 0, we show that this equation has a unique strong global solution for all x > 0 and we study some of its properties. Then we consider the following problem: What harvesting strategy maximizes the expected total discounted amount harvested (integrated over all future times)? We formulate this as a stochastic control problem. Then we show that there exists a constant optimal "harvest trigger value" x* epsilon (0, K) such that the optimal strategy is to do nothing if Xt < x* and to harvest Xt-x* if Xt > x*. This leads to an optimal population process Xt being reflected downward at x*. We find x* explicitly.

Environment↗
PubMed1984

Some population and epidemic models revisited.

Three problems of population and epidemic models formulated between ten and thirty years ago are reconsidered. In each case, a modified approach to the problem leads to its solution. For the two-sex population model, the solution of a Riccati equation results in an expression for the generating function of the process. The fully stochastic, as against the previously studied semistochastic, model of population growth with random catastrophes yields to hard analysis. Finally a generalized form of the general stochastic epidemic is solved using matrix geometric methods.

Biometry↗
PubMed1997

A branch-and-cut approach to physical mapping of chromosomes by unique end-probes.

A fundamental problem in computational biology is the construction of physical maps of chromosomes from hybridization experiments between unique probes and clones of chromosome fragments in the presence of error. Alizadeh, Karp, Weisser and Zweig (Algorithmica 13:1/2, 52-76, 1995) first considered a maximum-likelihood model of the problem that is equivalent to finding an ordering of the probes that minimizes a weighted sum of errors and developed several effective heuristics. We show that by exploiting information about the end-probes of clones, this model can be formulated as a Weighted Betweenness Problem. This affords the significant advantage of allowing the well-developed tools of integer linear-programming and branch-and-cut algorithms to be brought to bear on physical mapping, enabling us for the first time to solve small mapping instances to optimality even in the presence of high error. We also show that by combining the optimal solution of many small overlapping Betweenness Problems, one can effectively screen errors from larger instances and solve the edited instance to optimality as a Hamming-Distance Traveling Salesman Problem. This suggests a new approach, a Betweenness-Traveling Salesman hybrid, for constructing physical maps.

Chromosome Mapping↗
PubMed2001

Cluster-Rasch models for microarray gene expression data.

BACKGROUND: We propose two different formulations of the Rasch statistical models to the problem of relating gene expression profiles to the phenotypes. One formulation allows us to investigate whether a cluster of genes with similar expression profiles is related to the observed phenotypes; this model can also be used for future prediction. The other formulation provides an alternative way of identifying genes that are over- or underexpressed from their expression levels in tissue or cell samples of a given tissue or cell type. RESULTS: We illustrate the methods on available datasets of a classification of acute leukemias and of 60 cancer cell lines. For tumor classification, the results are comparable to those previously obtained. For the cancer cell lines dataset, we found four clusters of genes that are related to drug response for many of the 90 drugs that we considered. In addition, for each type of cell line, we identified genes that are over- or underexpressed relative to other genes. CONCLUSIONS: The cluster-Rasch model provides a probabilistic model for describing gene expression patterns across samples and can be used to relate gene expression profiles to phenotypes.

Acute Disease↗
PubMed1995

Improved cationic lipid formulations for in vivo gene therapy.

The problem of assessing in vivo activity of gene delivery systems is complex. The reporter gene must be carefully chosen depending on the application. Plasmids with strong promoters, enhancers and other elements that optimize transcription and translation should be employed, such as the CMVint and pCIS-CAT constructs. Formulation aspects of cationic lipid-DNA complexes are being studied in several laboratories, and the physical properties and molecular organization of the complexes are being elucidated. Likewise, studies on the mechanism of DNA delivery with cationic lipids are accumulating which support the basic concept that the complexes fuse with biological membranes leading to the entry of intact DNA into the cytoplasm. Naked plasmid DNA administered by various routes is expressed at significant levels in vivo. This observation is not restricted to skeletal and heart muscle, but has been observed in lung, dermis, and in undefined tissues following intravenous administration. Most of the widely available cationic lipids, including Lipofectin, Lipofectamine and DC-cholesterol have a very poor ability to enhance DNA expression above the baseline naked DNA level, at least in lung. In this report we have revealed a novel cationic lipid, DLRIE, which can significantly enhance CAT expression in mouse lung by 25-fold above the naked DNA level. Other compounds are currently being evaluated which can enhance the naked DNA expression even higher. Plasmid vector improvements have led to further increase in in vivo lung expression, so that the net improvement is > 5,000-fold. Results of this nature are advancing the pharmaceutical gene therapy opportunities for synthetic cationic lipid based gene delivery systems.

Animals↗
PubMed2004

A pulmonary formulation of L-dopa enhances its effectiveness in a rat model of Parkinson's disease.

The efficacy of oral L-dopa becomes problematic with the progression of Parkinson's disease, due in large part to a lost ability to accommodate L-dopa's inherently poor pharmacokinetics. Pulmonary delivery represents a novel approach to reducing this problem. L-dopa was formulated into inhalable (Alkermes AIR) particles, and its pharmacokinetics and pharmacodynamics compared with those of an oral formulation. Pulmonary administration of L-dopa (2 mg) to rats resulted in a rapid elevation of plasma levels (C(max) = 4.8 +/- 1.10 microg/ml at 2 min), whereas oral administration of L-dopa produced a much delayed and lower C(max) (1.8 +/- 0.40 microg/ml at 30 min). In a rat model of Parkinson's disease (unilateral 6-hydroxydopamine lesion), the pulmonary formulation of L-dopa (0.5-2.0 mg) yielded more rapid and robust elevations in striatal L-dopa, dopamine, and dihydroxyphenylacetic acid levels, as well as 2.5 to 3.7 times as many c-fos-expressing striatal neurons. Moreover, motor function was significantly improved by 10 min after administration, with peak improvements occurring within 15 to 30 min. In contrast, considerably higher doses (6.8-10 mg) of orally administered L-dopa took over three times longer to produce similar effects. These results suggest that an inhalable formulation of l-dopa has superior pharmacokinetic properties and may provide patients with a more effective form of rescue therapy as well as being a reliable adjuvant or replacement for first-line oral therapy.

Administration, Inhalation↗
PubMed1987

Optimization of beam weights under dose-volume restrictions.

A basic problem in treatment planning is the selection of weights for a set of beams which will yield the largest tumor dose under constraints limiting the doses received in specified fractions of different normal tissue structures. This report describes a method for formulating and solving this optimization problem as a combinatorial linear program. An illustration is provided by a problem in planning treatment of a thoracic tumor, in which no more than 1/2 or 2/3 of the lung is permitted to receive greater than 20 Gy and no part of the spinal cord allowed to receive greater than 45 Gy. The optimization technique was applied to this example to determine how the maximum tumor dose is affected by changes in the normal tissue constraints and the addition of a tumor dose homogeneity restriction. The linear programming technique yielded a rigorous and efficient determination of the beam weights for the thoracic plan considered. An exhaustive specification of all the underlying linear programs allows problems of moderate dimensions to be solved, while developments in mathematical programming and computer processing suggest approaches to problems of greater complexity.

Humans↗
PubMed2006

Dense photometric stereo: a Markov random field approach.

We address the problem of robust normal reconstruction by dense photometric stereo, in the presence of complex geometry, shadows, highlight, transparencies, variable attenuation in light intensities, and inaccurate estimation in light directions. The input is a dense set of noisy photometric images, conveniently captured by using a very simple set-up consisting of a digital video camera, a reflective mirror sphere, and a handheld spotlight. We formulate the dense photometric stereo problem as a Markov network and investigate two important inference algorithms for Markov Random Fields (MRFs)--graph cuts and belief propagation--to optimize for the most likely setting for each node in the network. In the graph cut algorithm, the MRF formulation is translated into one of energy minimization. A discontinuity-preserving metric is introduced as the compatibility function, which allows alpha-expansion to efficiently perform the maximum a posteriori (MAP) estimation. Using the identical dense input and the same MRF formulation, our tensor belief propagation algorithm recovers faithful normal directions, preserves underlying discontinuities, improves the normal estimation from one of discrete to continuous, and drastically reduces the storage requirement and running time. Both algorithms produce comparable and very faithful normals for complex scenes. Although the discontinuity-preserving metric in graph cuts permits efficient inference of optimal discrete labels with a theoretical guarantee, our estimation algorithm using tensor belief propagation converges to comparable results, but runs faster because very compact messages are passed and combined. We present very encouraging results on normal reconstruction. A simple algorithm is proposed to reconstruct a surface from a normal map recovered by our method. With the reconstructed surface, an inverse process, known as relighting in computer graphics, is proposed to synthesize novel images of the given scene under user-specified light source and direction. The synthesis is made to run in real time by exploiting the state-of-the-art graphics processing unit (GPU). Our method offers many unique advantages over previous relighting methods and can handle a wide range of novel light sources and directions.

Algorithms↗
PubMedDate not supplied

Behavioral and emotional disturbances in the offspring of depressed parents with anger attacks.

BACKGROUND: To examine the emotional and behavioral characteristics of the offspring of depressed parents with and without anger attacks. METHODS: Forty-three parents who met criteria for major depressive disorder (MDD) completed the Achenbach Child Behavior Checklist - Parent Report Version (CBCL) for each of their birth children (n = 58, age range 6-17 years). Unpaired t tests were used to evaluate the CBCL scale score differences between children of parents with and children of parents without anger attacks. Baseline demographics and clinical differences between the two groups of parents were also evaluated. RESULTS: Parents with anger attacks had a significantly younger age of onset of MDD. Offspring of depressed parents with anger attacks were found to have significantly lower social and school competency scale scores and higher scores for delinquency, attention problems, and aggressive behavior. In addition, this group was found to have a significantly higher total T score (a global measure of psychopathology). CONCLUSIONS: There are some important differences between offspring of depressed parents with and without anger attacks. This finding may be important in identifying and formulating intervention strategies for childhood problems in the offspring of depressed parents.

Achievement↗
PubMedDate not supplied

[From scientific evidence to operative practice: towards a model of occupational medicine based on on efficacy evidence].

There is increasing interest in improving health care practice and in providing evidence-based health care, that is, care in which different stakeholders consistently consider research evidence when making decisions. Quality of health care is presently viewed as a goal towards which different health care settings are geared. In comparison with this approach and in spite of the large development potentialities, occupational health practice is only at the beginning of the process. ILO convention No. 161 already pointed out the need to provide customers with quality-oriented services and evidence-based services. Occupational health practice can be analysed by means of a general system model already established for health care systems including input (structure, management, personnel, equipment), process (activities, performance), output (advice, recommendation), outcome (good life quality, sickness absence, work ability). All these elements can be critically measured with appropriate indicators to evaluate their efficacy. Despite general agreement about the importance of such analysis, there is a lack of data on the efficacy of prevention programmes. According to the evidence-based medicine model, which is commonly used by many other medical specialties, occupational health physicians could adopt a similar approach in order to implement more efficacious interventions. The evidence-based paradigm consists in the conscientious, explicit and judicious use of available best evidence in making decisions about health care problems. The practice of evidence-based medicine means integrating individual expertise with the best current evidence from systematic research. Evidence-based occupational health should implement this innovative approach to evaluate and to improve the efficiency of prevention services by means of the ability to (i) formulate the questions on the problem; (ii) search for scientific evidence; (iii) critically evaluate scientific evidence; (iv) use evidence as a key element for the decision process.

Evidence-Based Medicine↗