Application of data mining techniques in the prediction of coronary artery disease : use of anaesthesia time-series and patient risk factor data

The high morbidity and mortality associated with atherosclerotic coronary vascular disease (CVD) and its complications are being lessened by the increased knowledge of risk factors, effective preventative measures and proven therapeutic interventions. However, significant CVD morbidity remains and sudden cardiac death continues to be a presenting feature for some subsequently diagnosed with CVD. Coronary vascular disease is also the leading cause of anaesthesia related complications. Stress electrocardiography/exercise testing is predictive of 10 year risk of CVD events and the cardiovascular variables used to score this test are monitored peri-operatively. Similar physiological time-series datasets are being subjected to data mining methods for the prediction of medical diagnoses and outcomes. This study aims to find predictors of CVD using anaesthesia time-series data and patient risk factor data. Several pre-processing and predictive data mining methods are applied to this data. Physiological time-series data related to anaesthetic procedures are subjected to pre-processing methods for removal of outliers, calculation of moving averages as well as data summarisation and data abstraction methods. Feature selection methods of both wrapper and filter types are applied to derived physiological time-series variable sets alone and to the same variables combined with risk factor variables. The ability of these methods to identify subsets of highly correlated but non-redundant variables is assessed. The major dataset is derived from the entire anaesthesia population and subsets of this population are considered to be at increased anaesthesia risk based on their need for more intensive monitoring (invasive haemodynamic monitoring and additional ECG leads). Because of the unbalanced class distribution in the data, majority class under-sampling and Kappa statistic together with misclassification rate and area under the ROC curve (AUC) are used for evaluation of models generated using different prediction algorithms. The performance based on models derived from feature reduced datasets reveal the filter method, Cfs subset evaluation, to be most consistently effective although Consistency derived subsets tended to slightly increased accuracy but markedly increased complexity. The use of misclassification rate (MR) for model performance evaluation is influenced by class distribution. This could be eliminated by consideration of the AUC or Kappa statistic as well by evaluation of subsets with under-sampled majority class. The noise and outlier removal pre-processing methods produced models with MR ranging from 10.69 to 12.62 with the lowest value being for data from which both outliers and noise were removed (MR 10.69). For the raw time-series dataset, MR is 12.34. Feature selection results in reduction in MR to 9.8 to 10.16 with time segmented summary data (dataset F) MR being 9.8 and raw time-series summary data (dataset A) being 9.92. However, for all time-series only based datasets, the complexity is high. For most pre-processing methods, Cfs could identify a subset of correlated and non-redundant variables from the time-series alone datasets but models derived from these subsets are of one leaf only. MR values are consistent with class distribution in the subset folds evaluated in the n-cross validation method. For models based on Cfs selected time-series derived and risk factor (RF) variables, the MR ranges from 8.83 to 10.36 with dataset RF_A (raw time-series data and RF) being 8.85 and dataset RF_F (time segmented time-series variables and RF) being 9.09. The models based on counts of outliers and counts of data points outside normal range (Dataset RF_E) and derived variables based on time series transformed using Symbolic Aggregate Approximation (SAX) with associated time-series pattern cluster membership (Dataset RF_ G) perform the least well with MR of 10.25 and 10.36 respectively. For coronary vascular disease prediction, nearest neighbour (NNge) and the support vector machine based method, SMO, have the highest MR of 10.1 and 10.28 while logistic regression (LR) and the decision tree (DT) method, J48, have MR of 8.85 and 9.0 respectively. DT rules are most comprehensible and clinically relevant. The predictive accuracy increase achieved by addition of risk factor variables to time-series variable based models is significant. The addition of time-series derived variables to models based on risk factor variables alone is associated with a trend to improved performance. Data mining of feature reduced, anaesthesia time-series variables together with risk factor variables can produce compact and moderately accurate models able to predict coronary vascular disease. Decision tree analysis of time-series data combined with risk factor variables yields rules which are more accurate than models based on time-series data alone. The limited additional value provided by electrocardiographic variables when compared to use of risk factors alone is similar to recent suggestions that exercise electrocardiography (exECG) under standardised conditions has limited additional diagnostic value over risk factor analysis and symptom pattern. The effect of the pre-processing used in this study had limited effect when time-series variables and risk factor variables are used as model input. In the absence of risk factor input, the use of time-series variables after outlier removal and time series variables based on physiological variable values’ being outside the accepted normal range is associated with some improvement in model performance.

Land Sales Act 1984: The time limit for an application for exemption

The decision of Wilson J in Wan and Ors v NPD Property Development Pty Ltd [2004] QSC 232 also concerned the operation of the Land Sales Act 1984 (Qld) (‘the Act’). As previously noted, s 8(1) of the Act provides that a proposed allotment of freehold land might be sold only in certain circumstances. An agreement made in contravention of s 8(1) is void. Section 19 allows a purchaser (and others) to apply for an exemption from any of the provisions of Pt 2. By s 19(6), notwithstanding s 8, a person may agree to sell a proposed allotment if the instrument that binds a person to purchase the proposed allotment is conditional upon the grant of an exemption. By s 19(7) an application for exemption must be made ‘within 30 days after the event that marks the entry of a purchaser upon the purchase of the proposed allotment.’

Interim bills and costs assessment : was the application in or out of time?

This article examines the decision in Turner v Mitchells Solicitors [2011] QDC 61 and the issue whether an application for assessment of costs under an interim bill at the time of a final bill is subject to the usual 12-month restriction.

Shrinkage empirical likelihood estimator in longitudinal analysis with time-dependent covariates-application to modeling the health of Filipino children

The method of generalized estimating equations (GEE) is a popular tool for analysing longitudinal (panel) data. Often, the covariates collected are time-dependent in nature, for example, age, relapse status, monthly income. When using GEE to analyse longitudinal data with time-dependent covariates, crucial assumptions about the covariates are necessary for valid inferences to be drawn. When those assumptions do not hold or cannot be verified, Pepe and Anderson (1994, Communications in Statistics, Simulations and Computation 23, 939–951) advocated using an independence working correlation assumption in the GEE model as a robust approach. However, using GEE with the independence correlation assumption may lead to significant efficiency loss (Fitzmaurice, 1995, Biometrics 51, 309–317). In this article, we propose a method that extracts additional information from the estimating equations that are excluded by the independence assumption. The method always includes the estimating equations under the independence assumption and the contribution from the remaining estimating equations is weighted according to the likelihood of each equation being a consistent estimating equation and the information it carries. We apply the method to a longitudinal study of the health of a group of Filipino children.

Using informative priors in the estimation of mixtures over time with application to aerosol particle size distributions

The issue of using informative priors for estimation of mixtures at multiple time points is examined. Several different informative priors and an independent prior are compared using samples of actual and simulated aerosol particle size distribution (PSD) data. Measurements of aerosol PSDs refer to the concentration of aerosol particles in terms of their size, which is typically multimodal in nature and collected at frequent time intervals. The use of informative priors is found to better identify component parameters at each time point and more clearly establish patterns in the parameters over time. Some caveats to this finding are discussed.

Non-market use and non-use values for preserving ecosystem services over time : a choice experiment application to coral reef ecosystems in New Caledonia

Non-use values (i.e. economic values assigned by individuals to ecosystem goods and services unrelated to current or future uses) provide one of the most compelling incentives for the preservation of ecosystems and biodiversity. Assessing the non-use values of non-users is relatively straightforward using stated preference methods, but the standard approaches for estimating non-use values of users (stated decomposition) have substantial shortcomings which undermine the robustness of their results. In this paper, we propose a pragmatic interpretation of non-use values to derive estimates that capture their main dimensions, based on the identification of a willingness to pay for ecosystem protection beyond one's expected life. We empirically test our approach using a choice experiment conducted on coral reef ecosystem protection in two coastal areas in New Caledonia with different institutional, cultural, environmental and socio-economic contexts. We compute individual willingness to pay estimates, and derive individual non-use value estimates using our interpretation. We find that, a minima, estimates of non-use values may comprise between 25 and 40% of the mean willingness to pay for ecosystem preservation, less than has been found in most studies.

Theoretical Description of Time-Resolved Photoemission Spectroscopy: Application to Pump-Probe Experiments

The theory for time-resolved, pump-probe, photoemission spectroscopy and other pump-probe experiments is developed. The formal development is completely general, incorporating all of the nonequilibrium effects of the pump pulse and the finite time width of the probe pulse, and including possibilities for taking into account band structure and matrix element effects, surface states, and the interaction of the photoexcited electrons with the system leading to corrections to the sudden approximation. We also illustrate the effects of windowing that arise from the finite width of the probe pulse in a simple model system by assuming the quasiequilibrium approximation.

Effect of foliar herbicides on the germination and viability of Siam weed (Chromolaena odorata) seeds located on plants at the time of application.

This paper reports a field study undertaken to determine if the foliar application of herbicides fluroxypyr (150 mL 100 L-1 a.i.) and metsulfuron-methyl (12 g 100 L-1 a.i.) were capable of reducing the germination and viability of Chromolaena odorata (L.) R.M.King & H.Rob. (Siam weed) seeds at three different stages of maturity. After foliar application of fluroxypyr germination of mature seeds was reduced by 88% and intermediate and immature seeds were reduced by 100%, compared to the control. Fluroxypyr also reduced the viability of mature, intermediate and immature seeds by 79, 89 and 67% respectively, compared to the control. Metsulfuron-methyl reduced germination of intermediate and immature seeds by 53 and 99% respectively compared to the control. Viability was also reduced by 74 and 96% respectively, compared to the control. Mature seeds were not affected by metsulfuron-methyl as germination and viability increased by 2% and 1% respectively, as compared to the control. These results show that these herbicides are capable of reducing the amount of viable seed entering the seed bank. However depending on the treatment and stage of seed development a percentage of seeds on the plants will remain viable and contribute to the seed bank. This information is of value to Siam weed eradication teams as plants are most easily located and subsequently treated at the time of flowering. Knowledge of the impact of control methods on seeds at various stages of development will help determine the most suitable chemical control option for a given situation.

Application of the Conjugate Gradient Method to a Problem on Minimum Time Orbit Transfer

This correspondence considers the problem of optimally controlling the thrust steering angle of an ion-propelled spaceship so as to effect a minimum time coplanar orbit transfer from the mean orbital distance of Earth to mean Martian and Venusian orbital distances. This problem has been modelled as a free terminal time-optimal control problem with unbounded control variable and with state variable equality constraints at the final time. The problem has been solved by the penalty function approach, using the conjugate gradient algorithm. In general, the optimal solution shows a significant departure from earlier work. In particular, the optimal control in the case of Earth-Mars orbit transfer, during the initial phase of the spaceship's flight, is found to be negative, resulting in the motion of the spaceship within the Earth's orbit for a significant fraction of the total optimized orbit transfer time. Such a feature exhibited by the optimal solution has not been reported at all by earlier investigators of this problem.

Accurate mass-based analysis in human sport doping control : Application of liquid chromatography - time-of-flight mass spectrometry

Human sport doping control analysis is a complex and challenging task for anti-doping laboratories. The List of Prohibited Substances and Methods, updated annually by World Anti-Doping Agency (WADA), consists of hundreds of chemically and pharmacologically different low and high molecular weight compounds. This poses a considerable challenge for laboratories to analyze for them all in a limited amount of time from a limited sample aliquot. The continuous expansion of the Prohibited List obliges laboratories to keep their analytical methods updated and to research new available methodologies. In this thesis, an accurate mass-based analysis employing liquid chromatography - time-of-flight mass spectrometry (LC-TOFMS) was developed and validated to improve the power of doping control analysis. New analytical methods were developed utilizing the high mass accuracy and high information content obtained by TOFMS to generate comprehensive and generic screening procedures. The suitability of LC-TOFMS for comprehensive screening was demonstrated for the first time in the field with mass accuracies better than 1 mDa. Further attention was given to generic sample preparation, an essential part of screening analysis, to rationalize the whole work flow and minimize the need for several separate sample preparation methods. Utilizing both positive and negative ionization allowed the detection of almost 200 prohibited substances. Automatic data processing produced a Microsoft Excel based report highlighting the entries fulfilling the criteria of the reverse data base search (retention time (RT), mass accuracy, isotope match). The quantitative performance of LC-TOFMS was demonstrated with morphine, codeine and their intact glucuronide conjugates. After a straightforward sample preparation the compounds were analyzed directly without the need for hydrolysis, solvent transfer, evaporation or reconstitution. The hydrophilic interaction technique (HILIC) provided good chromatographic separation, which was critical for the morphine glucuronide isomers. A wide linear range (50-5000 ng/ml) with good precision (RSD<10%) and accuracy (±10%) was obtained, showing comparable or better performance to other methods used. In-source collision-induced dissociation (ISCID) allowed confirmation analysis with three diagnostic ions with a median mass accuracy of 1.08 mDa and repeatable ion ratios fulfilling WADA s identification criteria. The suitability of LC-TOFMS for screening of high molecular weight doping agents was demonstrated with plasma volume expanders (PVE), namely dextran and hydroxyethylstarch (HES). Specificity of the assay was improved, since interfering matrix compounds were removed by size exclusion chromatography (SEC). ISCID produced three characteristic ions with an excellent mean mass accuracy of 0.82 mDa at physiological concentration levels. In summary, by combining TOFMS with a proper sample preparation and chromatographic separation, the technique can be utilized extensively in doping control laboratories for comprehensive screening of chemically different low and high molecular weight compounds, for quantification of threshold substances and even for confirmation. LC-TOFMS rationalized the work flow in doping control laboratories by simplifying the screening scheme, expediting reporting and minimizing the analysis costs. Therefore LC-TOFMS can be exploited widely in doping control, and the need for several separate analysis techniques is reduced.

Redundancy resolution using a tractrix and its application to real-time simulations of hyper-redundant manipulators, snakes and tying of knots

To realistically simulate the motion of flexible objects such as ropes, strings, snakes, or human hair,one strategy is to discretise the object into a large number of small rigid links connected by rotary or spherical joints. The discretised system is highly redundant and the rotations at the joints (or the motion of the other links) for a desired Cartesian motion of the end of a link cannot be solved uniquely. In this paper, we propose a novel strategy to resolve the redundancy in such hyper-redundant systems.We make use of the classical tractrix curve and its attractive features. For a desired Cartesian motion of the `head'of a link, the `tail' of the link is moved according to a tractrix,and recursively all links of the discretised objects are moved along different tractrix curves. We show that the use of a tractrix curve leads to a more `natural' motion of the entire object since the motion is distributed uniformly along the entire object with the displacements tending to diminish from the `head' to the `tail'. We also show that the computation of the motion of the links can be done in real time since it involves evaluation of simple algebraic, trigonometric and hyperbolic functions. The strategy is illustrated by simulations of a snake, tying of knots with a rope and a solution of the inverse kinematics of a planar hyper-redundant manipulator.

Modeling Time-Varying Aggregate Interference in Cognitive Radio Systems, and Application to Primary Exclusive Zone Design

Accurately characterizing the time-varying interference caused to the primary users is essential in ensuring a successful deployment of cognitive radios (CR). We show that the aggregate interference at the primary receiver (PU-Rx) from multiple, randomly located cognitive users (CUs) is well modeled as a shifted lognormal random process, which is more accurate than the lognormal and the Gaussian process models considered in the literature, even for a relatively dense deployment of CUs. It also compares favorably with the asymptotically exact stable and symmetric truncated stable distribution models, except at high CU densities. Our model accounts for the effect of imperfect spectrum sensing, which depends on path-loss, shadowing, and small-scale fading of the link from the primary transmitter to the CU; the interweave and underlay modes or CR operation, which determine the transmit powers of the CUs; and time-correlated shadowing and fading of the links from the CUs to the PU-Rx. It leads to expressions for the probability distribution function, level crossing rate, and average exceedance duration. The impact of cooperative spectrum sensing is also characterized. We validate the model by applying it to redesign the primary exclusive zone to account for the time-varying nature of interference.