A review of dynamic Bayesian network techniques with applications in healthcare risk modelling

Coping with an ageing population is a major concern for healthcare organisations around the world. The average cost of hospital care is higher than social care for older and terminally ill patients. Moreover, the average cost of social care increases with the age of the patient. Therefore, it is important to make efficient and fair capacity planning which also incorporates patient centred outcomes. Predictive models can provide predictions which their accuracy can be understood and quantified. Predictive modelling can help patients and carers to get the appropriate support services, and allow clinical decision-makers to improve care quality and reduce the cost of inappropriate hospital and Accident and Emergency admissions. The aim of this study is to provide a review of modelling techniques and frameworks for predictive risk modelling of patients in hospital, based on routinely collected data such as the Hospital Episode Statistics database. A number of sub-problems can be considered such as Length-of-Stay and End-of-Life predictive modelling. The methodologies in the literature are mainly focused on addressing the problems using regression methods and Markov models, and the majority lack generalisability. In some cases, the robustness, accuracy and re-usability of predictive risk models have been shown to be improved using Machine Learning methods. Dynamic Bayesian Network techniques can represent complex correlations models and include small probabilities into the solution. The main focus of this study is to provide a review of major time-varying Dynamic Bayesian Network techniques with applications in healthcare predictive risk modelling.

Assessing residual reasoning ability in overtly non-communicative patients using fMRI

It is now well established that some patients who are diagnosed as being in a vegetative state or a minimally conscious state show reliable signs of volition that may only be detected by measuring neural responses. A pertinent question is whether these patients are also capable of logical thought. Here, we validate an fMRI paradigm that can detect the neural fingerprint of reasoning processes and moreover, can confirm whether a participant derives logical answers. We demonstrate the efficacy of this approach in a physically non-communicative patient who had been shown to engage in mental imagery in response to simple audi- tory instructions. Our results demonstrate that this individual retains a remarkable capacity for higher cogni- tion, engaging in the reasoning task and deducing logical answers. We suggest that this approach is suitable for detecting residual reasoning ability using neural responses and could readily be adapted to assess other aspects of cognition.

Avaliação e correlação de parâmetros físicos e mecânicos de um solo residual granítico

Os solos residuais mostram divergências em relação aos solos transportados modelados pelas teorias da Mecânica dos Solos. Estas divergências são em grande parte devido a uma estrutura de cimentação herdada da rocha mãe. Este estudo foi baseado nos resultados obtidos em sondagens mecânicas e ensaios de penetração dinâmica, estática e laboratoriais e consistiu na avaliação e correlação dos parâmetros que determinam o comportamento geomecânico do terreno, como a resistência e a deformabilidade.

Separating sequential equilibrium in a Bayesian international duopoly

We consider two Cournot firms, one located in the home country and the other in the foreign country, producing substitute goods for consumption in a third country. We suppose that neither the home government nor the foreign firm know the costs of the home firm, while the foreign firm cost is common knowledge. We determine the separating sequential equilibrium outputs.

Hydrogeophysical data integration at larger scales: Application of Bayesian sequential simulation for the characterization of heterogeneous alluvial aquifers

Knowledge of the spatial distribution of hydraulic conductivity (K) within an aquifer is critical for reliable predictions of solute transport and the development of effective groundwater management and/or remediation strategies. While core analyses and hydraulic logging can provide highly detailed information, such information is inherently localized around boreholes that tend to be sparsely distributed throughout the aquifer volume. Conversely, larger-scale hydraulic experiments like pumping and tracer tests provide relatively low-resolution estimates of K in the investigated subsurface region. As a result, traditional hydrogeological measurement techniques contain a gap in terms of spatial resolution and coverage, and they are often alone inadequate for characterizing heterogeneous aquifers. Geophysical methods have the potential to bridge this gap. The recent increased interest in the application of geophysical methods to hydrogeological problems is clearly evidenced by the formation and rapid growth of the domain of hydrogeophysics over the past decade (e.g., Rubin and Hubbard, 2005).

Residual antimalarials in malaria patients from Tanzania--implications on drug efficacy assessment and spread of parasite resistance.

Repeated antimalarial treatment for febrile episodes and self-treatment are common in malaria-endemic areas. The intake of antimalarials prior to participating in an in vivo study may alter treatment outcome and affect the interpretation of both efficacy and safety outcomes. We report the findings from baseline plasma sampling of malaria patients prior to inclusion into an in vivo study in Tanzania and discuss the implications of residual concentrations of antimalarials in this setting. In an in vivo study conducted in a rural area of Tanzania in 2008, baseline plasma samples from patients reporting no antimalarial intake within the last 28 days were screened for the presence of 14 antimalarials (parent drugs or metabolites) using liquid chromatography-tandem mass spectrometry. Among the 148 patients enrolled, 110 (74.3%) had at least one antimalarial in their plasma: 80 (54.1%) had lumefantrine above the lower limit of calibration (LLC = 4 ng/mL), 7 (4.7%) desbutyl-lumefantrine (4 ng/mL), 77 (52.0%) sulfadoxine (0.5 ng/mL), 15 (10.1%) pyrimethamine (0.5 ng/mL), 16 (10.8%) quinine (2.5 ng/mL) and none chloroquine (2.5 ng/mL). The proportion of patients with detectable antimalarial drug levels prior to enrollment into the study is worrying. Indeed artemether-lumefantrine was supposed to be available only at government health facilities. Although sulfadoxine-pyrimethamine is only recommended for intermittent preventive treatment in pregnancy (IPTp), it was still widely used in public and private health facilities and sold in drug shops. Self-reporting of previous drug intake is unreliable and thus screening for the presence of antimalarial drug levels should be considered in future in vivo studies to allow for accurate assessment of treatment outcome. Furthermore, persisting sub-therapeutic drug levels of antimalarials in a population could promote the spread of drug resistance. The knowledge on drug pressure in a given population is important to monitor standard treatment policy implementation.

Absence of residual Hodgkin's disease demonstrated by PET/CT in a deceased organ donor.

With the current limited availability of organs for transplantation, it is important to consider marginal donor candidates, including survivors of potentially curable malignancies such as lymphoma. The absence of refractory/recurrent residual disease at the time of brain death can be difficult to establish. Therefore, it is critical to have objective data to decide whether to proceed or not with organ procurement and transplantation. We report a unique situation in which (18)F-fluorodeoxyglucose positron emission tomography (PET) was used to rule out Hodgkin's lymphoma recurrence in a 33-year-old, heart-beating, brain-dead, potential donor with a past history of Hodgkin's disease and a persistent mediastinal mass. PET showed no significant uptake in the mass, allowing organ donation and transplantation to occur. We present a new means of evaluating potential brain-dead donors with a past history of some lymphoma, whereby PET may help transplant physicians by optimizing donation safety while rationalizing the inclusion of marginal donors.

Toxic substances in blood: an analysis of current recommendations under a Bayesian (decision) approach

This article extends existing discussion in literature on probabilistic inference and decision making with respect to continuous hypotheses that are prevalent in forensic toxicology. As a main aim, this research investigates the properties of a widely followed approach for quantifying the level of toxic substances in blood samples, and to compare this procedure with a Bayesian probabilistic approach. As an example, attention is confined to the presence of toxic substances, such as THC, in blood from car drivers. In this context, the interpretation of results from laboratory analyses needs to take into account legal requirements for establishing the 'presence' of target substances in blood. In a first part, the performance of the proposed Bayesian model for the estimation of an unknown parameter (here, the amount of a toxic substance) is illustrated and compared with the currently used method. The model is then used in a second part to approach-in a rational way-the decision component of the problem, that is judicial questions of the kind 'Is the quantity of THC measured in the blood over the legal threshold of 1.5 μg/l?'. This is pointed out through a practical example.

An HPLC method for simultaneous determination of residual benomyl and MBC on apple foliage without cleanup

A simple High Performance Liquid Chromatograph (HPLC) method has been developed to identify benamyl (methyl 1- (butylcarbamoyl)-2-benzimidazole carbamate) and MBC (methyl 2-benzimidazole carbamat~ residues on apple leaves without cleanup. Sample leaves are freeze dried in a Mason jar and residues are then extracted by tumbling them in chloroform containing 5,000 microgram per milliliter of n-propyl isocyanate (PIC) at 10 C. To the extract, n-butyl isocyanate (BIC) was added at 5,000 microgram per milliliter and 20 microliter of this mixture injected onto the HPLC system. Separation is accomplished by the use of a Brownlee LiChrosorb silica gel column with a guard column and' operated with a mixed mobile phase consisting of chloroform and hexane (4:1) saturated with water. MBC, a degradation product of benomyl is identified if present as methyl l-(npropyl carbamoyl)-2-benzimidazole carbamate (MBC-n-PIC). Both benomyl and MBC-n-PIC can be detected with aKUltraviolet (UV) detector (280nm) at a concentration as low as 0.2 microgram per milliliter in apple leaves. The fate of benomyl on apple foliage after spray application of benomyl (Ben late 50 per cent wettable powder) was investigated by the method thus described. Benomyl quickly dissipated during the first 3-7 days, but the dissipatio'n sltowed down thereafter. In contrast, the concentration of MBC in leaves gradually increased after repeated applications of Benlate.

Using a Bayesian model for bankruptcy prediction : a comparative approach

The purpose of this study is to examine the impact of the choice of cut-off points, sampling procedures, and the business cycle on the accuracy of bankruptcy prediction models. Misclassification can result in erroneous predictions leading to prohibitive costs to firms, investors and the economy. To test the impact of the choice of cut-off points and sampling procedures, three bankruptcy prediction models are assessed- Bayesian, Hazard and Mixed Logit. A salient feature of the study is that the analysis includes both parametric and nonparametric bankruptcy prediction models. A sample of firms from Lynn M. LoPucki Bankruptcy Research Database in the U. S. was used to evaluate the relative performance of the three models. The choice of a cut-off point and sampling procedures were found to affect the rankings of the various models. In general, the results indicate that the empirical cut-off point estimated from the training sample resulted in the lowest misclassification costs for all three models. Although the Hazard and Mixed Logit models resulted in lower costs of misclassification in the randomly selected samples, the Mixed Logit model did not perform as well across varying business-cycles. In general, the Hazard model has the highest predictive power. However, the higher predictive power of the Bayesian model, when the ratio of the cost of Type I errors to the cost of Type II errors is high, is relatively consistent across all sampling methods. Such an advantage of the Bayesian model may make it more attractive in the current economic environment. This study extends recent research comparing the performance of bankruptcy prediction models by identifying under what conditions a model performs better. It also allays a range of user groups, including auditors, shareholders, employees, suppliers, rating agencies, and creditors' concerns with respect to assessing failure risk.

Minimización de los residuos de esmalte en una planta de productos cerámicos a través del reciclado del agua residual

Tesis (Maestría en Ciencias con Especialidad en Ingeniería Ambiental) UANL

Determinación de las constantes cinéticas de nitrificación en una agua residual mixta (doméstica e industrial)

Tesis (Maestría en Ciencias con Especialidad en Ingeniería Ambiental) UANL