52 resultados para Multi-criterion Decision Analysis (MCDA)


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OBJECTIVE: This study aimed to assess the potential cost-effectiveness of testing patients with nephropathies for the I/D polymorphism before starting angiotensin-converting enzyme (ACE) inhibitor therapy, using a 3-year time horizon and a healthcare perspective. METHODS: We used a combination of a decision analysis and Markov modeling technique to evaluate the potential economic value of this pharmacogenetic test by preventing unfavorable treatment in patients with nephropathies. The estimation of the predictive value of the I/D polymorphism is based on a systematic review showing that DD carriers tend to respond well to ACE inhibitors, while II carriers seem not to benefit adequately from this treatment. Data on the ACE inhibitor effectiveness in nephropathy were derived from the REIN (Ramipril Efficacy in Nephropathy) trial. We calculated the number of patients with end-stage renal disease (ESRD) prevented and the differences in the incremental costs and incremental effect expressed as life-years free of ESRD. A probabilistic sensitivity analysis was conducted to determine the robustness of the results. RESULTS: Compared with unselective treatment, testing patients for their ACE genotype could save 12 patients per 1000 from developing ESRD during the 3 years covered by the model. As the mean net cost savings was euro 356,000 per 1000 patient-years, and 9 life-years free of ESRD were gained, selective treatment seems to be dominant. CONCLUSION: The study suggests that genetic testing of the I/D polymorphism in patients with nephropathy before initiating ACE therapy will most likely be cost-effective, even if the risk for II carriers to develop ESRD when treated with ACE inhibitors is only 1.4% higher than for DD carriers. Further studies, however, are required to corroborate the difference in treatment response between ACE genotypes, before genetic testing can be justified in clinical practice.

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Population coding is widely regarded as a key mechanism for achieving reliable behavioral decisions. We previously introduced reinforcement learning for population-based decision making by spiking neurons. Here we generalize population reinforcement learning to spike-based plasticity rules that take account of the postsynaptic neural code. We consider spike/no-spike, spike count and spike latency codes. The multi-valued and continuous-valued features in the postsynaptic code allow for a generalization of binary decision making to multi-valued decision making and continuous-valued action selection. We show that code-specific learning rules speed up learning both for the discrete classification and the continuous regression tasks. The suggested learning rules also speed up with increasing population size as opposed to standard reinforcement learning rules. Continuous action selection is further shown to explain realistic learning speeds in the Morris water maze. Finally, we introduce the concept of action perturbation as opposed to the classical weight- or node-perturbation as an exploration mechanism underlying reinforcement learning. Exploration in the action space greatly increases the speed of learning as compared to exploration in the neuron or weight space.

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The fuzzy analytical network process (FANP) is introduced as a potential multi-criteria-decision-making (MCDM) method to improve digital marketing management endeavors. Today’s information overload makes digital marketing optimization, which is needed to continuously improve one’s business, increasingly difficult. The proposed FANP framework is a method for enhancing the interaction between customers and marketers (i.e., involved stakeholders) and thus for reducing the challenges of big data. The presented implementation takes realities’ fuzziness into account to manage the constant interaction and continuous development of communication between marketers and customers on the Web. Using this FANP framework, the marketers are able to increasingly meet the varying requirements of their customers. To improve the understanding of the implementation, advanced visualization methods (e.g., wireframes) are used.

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OBJECTIVES Fontan failure (FF) represents a growing and challenging indication for paediatric orthotopic heart transplantation (OHT). The aim of this study was to identify predictors of the best mid-term outcome in OHT after FF. METHODS Twenty-year multi-institutional retrospective analysis on OHT for FF. RESULTS Between 1991 and 2011, 61 patients, mean age 15.0 ± 9.7 years, underwent OHT for failing atriopulmonary connection (17 patients = 27.8%) or total cavopulmonary connection (44 patients = 72.2%). Modality of FF included arrhythmia (14.8%), complex obstructions in the Fontan circuit (16.4%), protein-losing enteropathy (PLE) (22.9%), impaired ventricular function (31.1%) or a combination of the above (14.8%). The mean time interval between Fontan completion and OHT was 10.7 ± 6.6 years. Early FF occurred in 18%, requiring OHT 0.8 ± 0.5 years after Fontan. The hospital mortality rate was 18.3%, mainly secondary to infection (36.4%) and graft failure (27.3%). The mean follow-up was 66.8 ± 54.2 months. The overall Kaplan-Meier survival estimate was 81.9 ± 1.8% at 1 year, 73 ± 2.7% at 5 years and 56.8 ± 4.3% at 10 years. The Kaplan-Meier 5-year survival estimate was 82.3 ± 5.9% in late FF and 32.7 ± 15.0% in early FF (P = 0.0007). Late FF with poor ventricular function exhibited a 91.5 ± 5.8% 5-year OHT survival. PLE was cured in 77.7% of hospital survivors, but the 5-year Kaplan-Meier survival estimate in PLE was 46.3 ± 14.4 vs 84.3 ± 5.5% in non-PLE (P = 0.0147). Cox proportional hazards identified early FF (P = 0.0005), complex Fontan pathway obstruction (P = 0.0043) and PLE (P = 0.0033) as independent predictors of 5-year mortality. CONCLUSIONS OHT is an excellent surgical option for late FF with impaired ventricular function. Protein dispersion improves with OHT, but PLE negatively affects the mid-term OHT outcome, mainly for early infective complications.

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The study assessed the economic efficiency of different strategies for the control of post-weaning multi-systemic wasting syndrome (PMWS) and porcine circovirus type 2 subclinical infection (PCV2SI), which have a major economic impact on the pig farming industry worldwide. The control strategies investigated consisted on the combination of up to 5 different control measures. The control measures considered were: (1) PCV2 vaccination of piglets (vac); (2) ensuring age adjusted diet for growers (diets); (3) reduction of stocking density (stock); (4) improvement of biosecurity measures (bios); and (5) total depopulation and repopulation of the farm for the elimination of other major pathogens (DPRP). A model was developed to simulate 5 years production of a pig farm with a 3-weekly batch system and with 100 sows. A PMWS/PCV2SI disease and economic model, based on PMWS severity scores, was linked to the production model in order to assess disease losses. This PMWS severity scores depends on the combination post-weaning mortality, PMWS morbidity in younger pigs and proportion of PCV2 infected pigs observed on farms. The economic analysis investigated eleven different farm scenarios, depending on the number of risk factors present before the intervention. For each strategy, an investment appraisal assessed the extra costs and benefits of reducing a given PMWS severity score to the average score of a slightly affected farm. The net present value obtained for each strategy was then multiplied by the corresponding probability of success to obtain an expected value. A stochastic simulation was performed to account for uncertainty and variability. For moderately affected farms PCV2 vaccination alone was the most cost-efficient strategy, but for highly affected farms it was either PCV2 vaccination alone or in combination with biosecurity measures, with the marginal profitability between 'vac' and 'vac+bios' being small. Other strategies such as 'diets', 'vac+diets' and 'bios+diets' were frequently identified as the second or third best strategy. The mean expected values of the best strategy for a moderately and a highly affected farm were £14,739 and £57,648 after 5 years, respectively. This is the first study to compare economic efficiency of control strategies for PMWS and PCV2SI. The results demonstrate the economic value of PCV2 vaccination, and highlight that on highly affected farms biosecurity measures are required to achieve optimal profitability. The model developed has potential as a farm-level decision support tool for the control of this economically important syndrome.

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During the last 10 years several molecular markers have been established as useful tools among the armamentarium of a hematologist. As a consequence, the number of performed hematologic molecular analyses has immensely increased. Often, such tests replace or complement other laboratory methods. Molecular markers can be useful in many ways: they can serve for diagnostics, describe the prognostic profile, predict which types of drugs are indicated, and can be used for the therapeutic monitoring of the patient to indicate an adequate response or predict resistance or relapse of the disease. Many markers fulfill more than one of these aspects. Most important, however, is the right choice of analyses at the right time-points!

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Changes in marine net primary productivity (PP) and export of particulate organic carbon (EP) are projected over the 21st century with four global coupled carbon cycle-climate models. These include representations of marine ecosystems and the carbon cycle of different structure and complexity. All four models show a decrease in global mean PP and EP between 2 and 20% by 2100 relative to preindustrial conditions, for the SRES A2 emission scenario. Two different regimes for productivity changes are consistently identified in all models. The first chain of mechanisms is dominant in the low- and mid-latitude ocean and in the North Atlantic: reduced input of macro-nutrients into the euphotic zone related to enhanced stratification, reduced mixed layer depth, and slowed circulation causes a decrease in macro-nutrient concentrations and in PP and EP. The second regime is projected for parts of the Southern Ocean: an alleviation of light and/or temperature limitation leads to an increase in PP and EP as productivity is fueled by a sustained nutrient input. A region of disagreement among the models is the Arctic, where three models project an increase in PP while one model projects a decrease. Projected changes in seasonal and interannual variability are modest in most regions. Regional model skill metrics are proposed to generate multi-model mean fields that show an improved skill in representing observation-based estimates compared to a simple multi-model average. Model results are compared to recent productivity projections with three different algorithms, usually applied to infer net primary production from satellite observations.

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Image-based modeling of tumor growth combines methods from cancer simulation and medical imaging. In this context, we present a novel approach to adapt a healthy brain atlas to MR images of tumor patients. In order to establish correspondence between a healthy atlas and a pathologic patient image, tumor growth modeling in combination with registration algorithms is employed. In a first step, the tumor is grown in the atlas based on a new multi-scale, multi-physics model including growth simulation from the cellular level up to the biomechanical level, accounting for cell proliferation and tissue deformations. Large-scale deformations are handled with an Eulerian approach for finite element computations, which can operate directly on the image voxel mesh. Subsequently, dense correspondence between the modified atlas and patient image is established using nonrigid registration. The method offers opportunities in atlasbased segmentation of tumor-bearing brain images as well as for improved patient-specific simulation and prognosis of tumor progression.

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During the last decade, a multi-modal approach has been established in human experimental pain research for assessing pain thresholds and responses to various experimental pain modalities. Studies have concluded that differences in responses to pain stimuli are mainly related to variation between individuals rather than variation in response to different stimulus modalities. In a factor analysis of 272 consecutive volunteers (137 men and 135 women) who underwent tests with different experimental pain modalities, it was determined whether responses to different pain modalities represent distinct individual uncorrelated dimensions of pain perception. Volunteers underwent single painful electrical stimulation, repeated painful electrical stimulation (temporal summation), test for reflex receptive field, pressure pain stimulation, heat pain stimulation, cold pain stimulation, and a cold pressor test (ice water test). Five distinct factors were found representing responses to 5 distinct experimental pain modalities: pressure, heat, cold, electrical stimulation, and reflex-receptive fields. Each of the factors explained approximately 8% to 35% of the observed variance, and the 5 factors cumulatively explained 94% of the variance. The correlation between the 5 factors was near null (median ρ=0.00, range -0.03 to 0.05), with 95% confidence intervals for pairwise correlations between 2 factors excluding any relevant correlation. Results were almost similar for analyses stratified according to gender and age. Responses to different experimental pain modalities represent different specific dimensions and should be assessed in combination in future pharmacological and clinical studies to represent the complexity of nociception and pain experience.

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Survival after surgical treatment using competing-risk analysis has been previously examined in patients with prostate cancer (PCa). However, the combined effect of age and comorbidities has not been assessed in patients with high-risk PCa who might have heterogeneous rates of competing mortality despite the presence of aggressive disease.