871 resultados para Classifier Generalization Ability


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BACKGROUND: The estimation of physiologic ability and surgical stress (E-PASS) has been used to produce a numerical estimate of expected mortality and morbidity after elective gastrointestinal surgery. The aim of this study was to validate E-PASS in a selected cohort of patients requiring liver resections (LR). METHODS: In this retrospective study, E-PASS predictor equations for morbidity and mortality were applied to the prospective data from 243 patients requiring LR. The observed rates were compared with predicted rates using Fisher's exact test. The discriminative capability of E-PASS was evaluated using receiver-operating characteristic (ROC) curve analysis. RESULTS: The observed and predicted overall mortality rates were both 3.3% and the morbidity rates were 31.3 and 26.9%, respectively. There was a significant difference in the comprehensive risk scores for deceased and surviving patients (p = 0.043). However, the scores for patients with or without complications were not significantly different (p = 0.120). Subsequent ROC curve analysis revealed a poor predictive accuracy for morbidity. CONCLUSIONS: The E-PASS score seems to effectively predict mortality in this specific group of patients but is a poor predictor of complications. A new modified logistic regression might be required for LR in order to better predict the postoperative outcome.

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Aim of this paper is to evaluate the diagnostic contribution of various types of texture features in discrimination of hepatic tissue in abdominal non-enhanced Computed Tomography (CT) images. Regions of Interest (ROIs) corresponding to the classes: normal liver, cyst, hemangioma, and hepatocellular carcinoma were drawn by an experienced radiologist. For each ROI, five distinct sets of texture features are extracted using First Order Statistics (FOS), Spatial Gray Level Dependence Matrix (SGLDM), Gray Level Difference Method (GLDM), Laws' Texture Energy Measures (TEM), and Fractal Dimension Measurements (FDM). In order to evaluate the ability of the texture features to discriminate the various types of hepatic tissue, each set of texture features, or its reduced version after genetic algorithm based feature selection, was fed to a feed-forward Neural Network (NN) classifier. For each NN, the area under Receiver Operating Characteristic (ROC) curves (Az) was calculated for all one-vs-all discriminations of hepatic tissue. Additionally, the total Az for the multi-class discrimination task was estimated. The results show that features derived from FOS perform better than other texture features (total Az: 0.802+/-0.083) in the discrimination of hepatic tissue.

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Quantitative characterisation of carotid atherosclerosis and classification into symptomatic or asymptomatic is crucial in planning optimal treatment of atheromatous plaque. The computer-aided diagnosis (CAD) system described in this paper can analyse ultrasound (US) images of carotid artery and classify them into symptomatic or asymptomatic based on their echogenicity characteristics. The CAD system consists of three modules: a) the feature extraction module, where first-order statistical (FOS) features and Laws' texture energy can be estimated, b) the dimensionality reduction module, where the number of features can be reduced using analysis of variance (ANOVA), and c) the classifier module consisting of a neural network (NN) trained by a novel hybrid method based on genetic algorithms (GAs) along with the back propagation algorithm. The hybrid method is able to select the most robust features, to adjust automatically the NN architecture and to optimise the classification performance. The performance is measured by the accuracy, sensitivity, specificity and the area under the receiver-operating characteristic (ROC) curve. The CAD design and development is based on images from 54 symptomatic and 54 asymptomatic plaques. This study demonstrates the ability of a CAD system based on US image analysis and a hybrid trained NN to identify atheromatous plaques at high risk of stroke.

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In this paper, a computer-aided diagnostic (CAD) system for the classification of hepatic lesions from computed tomography (CT) images is presented. Regions of interest (ROIs) taken from nonenhanced CT images of normal liver, hepatic cysts, hemangiomas, and hepatocellular carcinomas have been used as input to the system. The proposed system consists of two modules: the feature extraction and the classification modules. The feature extraction module calculates the average gray level and 48 texture characteristics, which are derived from the spatial gray-level co-occurrence matrices, obtained from the ROIs. The classifier module consists of three sequentially placed feed-forward neural networks (NNs). The first NN classifies into normal or pathological liver regions. The pathological liver regions are characterized by the second NN as cyst or "other disease." The third NN classifies "other disease" into hemangioma or hepatocellular carcinoma. Three feature selection techniques have been applied to each individual NN: the sequential forward selection, the sequential floating forward selection, and a genetic algorithm for feature selection. The comparative study of the above dimensionality reduction methods shows that genetic algorithms result in lower dimension feature vectors and improved classification performance.

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This paper reviews research findings on entrepreneurial top management teams within the last 20 years. It concentrates on team-based management factors and their influence on a new venture’s growth and ability to raise capital. This paper integrates recent findings and provides an overview of the current state of research. Moreover, it contributes to the overall topic by proposing five clusters of major team-specific influences, derives determinants of success and failure, and reveals recommendations for further research.

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Plant species richness of permanent grasslands has often been found to be significantly associated with productivity. Concentrations of nutrients in biomass can give further insight into these productivity- plant species richness relationships, e.g. by reflecting land use or soil characteristics. However, the consistency of such relationships across different regions has rarely been taken into account, which might significantly compromise our potential for generalization. We recorded plant species richness and measured above-ground biomass and concentrations of nutrients in biomass in 295 grasslands in three regions in Germany that differ in soil and climatic conditions. Structural equation modelling revealed that nutrient concentrations were mostly indirectly associated with plant species richness via biomass production. However, negative associations between the concentrations of different nutrients and biomass and plant species richness differed considerably among regions. While in two regions, more than 40% of the variation in plant species richness could be attributed to variation in biomass, K, P, and to some degree also N concentrations, in the third region only 15% of the variation could be explained in this way. Generally, highest plant species richness was recorded in grasslands where N and P were co-limiting plant growth, in contrast to N or K (co-) limitation. But again, this pattern was not recorded in the third region. While for two regions land-use intensity and especially the application of fertilizers are suggested to be the main drivers causing the observed negative associations with productivity, in the third region the little variance accounted for, low species richness and weak relationships implied that former intensive grassland management, ongoing mineralization of peat and fluctuating water levels in fen grasslands have overruled effects of current land-use intensity and productivity. Finally, we conclude that regional replication is of major importance for studies seeking general insights into productivity-diversity relationships.

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BACKGROUND AND OBJECTIVES Quantitative sensory testing (QST) is widely used to investigate peripheral and central sensitization. However, the comparative performance of different QST for diagnostic or prognostic purposes is unclear. We explored the discriminative ability of different quantitative sensory tests in distinguishing between patients with chronic neck pain and pain-free control subjects and ranked these tests according to the extent of their association with pain hypersensitivity. METHODS We performed a case-control study in 40 patients and 300 control subjects. Twenty-six tests, including different modalities of pressure, heat, cold, and electrical stimulation, were used. As measures of discrimination, we estimated receiver operating characteristic curves and likelihood ratios. RESULTS The following quantitative sensory tests displayed the best discriminative value: (1) pressure pain threshold at the site of the most severe neck pain (fitted area under the receiver operating characteristic curve, 0.92), (2) reflex threshold to single electrical stimulation (0.90), (3) pain threshold to single electrical stimulation (0.89), (4) pain threshold to repeated electrical stimulation (0.87), and (5) pressure pain tolerance threshold at the site of the most severe neck pain (0.86). Only the first 3 could be used for both ruling in and out pain hypersensitivity. CONCLUSIONS Pressure stimulation at the site of the most severe pain and parameters of electrical stimulation were the most appropriate QST to distinguish between patients with chronic neck pain and asymptomatic control subjects. These findings may be used to select the tests in future diagnostic and longitudinal prognostic studies on patients with neck pain and to optimize the assessment of localized and spreading sensitization in chronic pain patients.

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The metacognitve ability to accurately estimate ones performance in a test, is assumed to be of central importance for initializing task-oriented effort. In addition activating adequate problem-solving strategies, and engaging in efficient error detection and correction. Although school children's' ability to estimate their own performance has been widely investigated, this was mostly done under highly-controlled, experimental set-ups including only one single test occasion. Method: The aim of this study was to investigate this metacognitive ability in the context of real achievement tests in mathematics. Developed and applied by a teacher of a 5th grade class over the course of a school year these tests allowed the exploration of the variability of performance estimation accuracy as a function of test difficulty. Results: Mean performance estimations were generally close to actual performance with somewhat less variability compared to test performance. When grouping the children into three achievement levels, results revealed higher accuracy of performance estimations in the high achievers compared to the low and average achievers. In order to explore the generalization of these findings, analyses were also conducted for the same children's tests in their science classes revealing a very similar pattern of results compared to the domain of mathematics. Discussion and Conclusion: By and large, the present study, in a natural environment, confirmed previous laboratory findings but also offered additional insights into the generalisation and the test dependency of students' performances estimations.

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This study proposes a VE that offers a reliable diagnosis of the stage of cognitive decline in dementia patients and assists the delay of this decline in terms of the visuo-constructional ability. The proposed VE, in the case of the assessment, presents a visuo-constructional completion task, which requires spatial perception, motor memory and the perception of the target object. In the case of the rehabilitation the VE uses sound as audio-feedback that, with the aid of the music perception, tends to develop an enhancement in the visuo-construction ability of the dementia patients that can be generalized even outside of the VE. The study examined 30 subjects that were normal controls (N), 30 patients suffering from memory disorders (Age-Associated Memory Impairment--AAMI) and 30 suffering from Alzheimer's Disease (AD). The results showed that there is a significant correlation between the performance in the visuo-constructional task and the dementia diagnosis. It also seems that the visuo-constructional ability of the (AD) patients can be statistically improved by the audio experience in the VE. The empirical results of this study offer an alternative diagnosis and treatment of dementia patients and could share some light in the brain sub-systems that are responsible for the visuo-constructional ability. Further studies are required in order to investigate the nature of this phenomenon more.

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People with synaesthesia show an enhanced memory relative to demographically matched controls. The most obvious explanation for this is that the ‘extra’ perceptual experiences lead to richer encoding and retrieval opportunities of stimuli which induce synaesthesia (typically verbal stimuli). Although there is some evidence for this, it is unlikely to be the whole explanation. For instance, not all stimuli which trigger synaesthesia are better remembered (e.g., digit span) and some stimuli which do not trigger synaesthesia are better remembered. In fact, synaesthetes tend to have better visual memory than verbal memory. We suggest that enhanced memory in synaesthesia is linked to wider changes in cognitive systems at the interface of perception and memory and link this to recent findings in the neuroscience of memory.