901 resultados para Uninterpretable features


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Seizure freedom in patients suffering from pharmacoresistant epilepsies is still not achieved in 20–30% of all cases. Hence, current therapies need to be improved, based on a more complete understanding of ictogenesis. In this respect, the analysis of functional networks derived from intracranial electroencephalographic (iEEG) data has recently become a standard tool. Functional networks however are purely descriptive models and thus are conceptually unable to predict fundamental features of iEEG time-series, e.g., in the context of therapeutical brain stimulation. In this paper we present some first steps towards overcoming the limitations of functional network analysis, by showing that its results are implied by a simple predictive model of time-sliced iEEG time-series. More specifically, we learn distinct graphical models (so called Chow–Liu (CL) trees) as models for the spatial dependencies between iEEG signals. Bayesian inference is then applied to the CL trees, allowing for an analytic derivation/prediction of functional networks, based on thresholding of the absolute value Pearson correlation coefficient (CC) matrix. Using various measures, the thus obtained networks are then compared to those which were derived in the classical way from the empirical CC-matrix. In the high threshold limit we find (a) an excellent agreement between the two networks and (b) key features of periictal networks as they have previously been reported in the literature. Apart from functional networks, both matrices are also compared element-wise, showing that the CL approach leads to a sparse representation, by setting small correlations to values close to zero while preserving the larger ones. Overall, this paper shows the validity of CL-trees as simple, spatially predictive models for periictal iEEG data. Moreover, we suggest straightforward generalizations of the CL-approach for modeling also the temporal features of iEEG signals.

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Reproducible definition and quantification of imaging biomarkers is essential. We evaluated a fully automatic MR-based segmentation method by comparing it to manually defined sub-volumes by experienced radiologists in the TCGA-GBM dataset, in terms of sub-volume prognosis and association with VASARI features. MRI sets of 109 GBM patients were downloaded from the Cancer Imaging archive. GBM sub-compartments were defined manually and automatically using the Brain Tumor Image Analysis (BraTumIA). Spearman's correlation was used to evaluate the agreement with VASARI features. Prognostic significance was assessed using the C-index. Auto-segmented sub-volumes showed moderate to high agreement with manually delineated volumes (range (r): 0.4 - 0.86). Also, the auto and manual volumes showed similar correlation with VASARI features (auto r = 0.35, 0.43 and 0.36; manual r = 0.17, 0.67, 0.41, for contrast-enhancing, necrosis and edema, respectively). The auto-segmented contrast-enhancing volume and post-contrast abnormal volume showed the highest AUC (0.66, CI: 0.55-0.77 and 0.65, CI: 0.54-0.76), comparable to manually defined volumes (0.64, CI: 0.53-0.75 and 0.63, CI: 0.52-0.74, respectively). BraTumIA and manual tumor sub-compartments showed comparable performance in terms of prognosis and correlation with VASARI features. This method can enable more reproducible definition and quantification of imaging based biomarkers and has potential in high-throughput medical imaging research.

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The coronary collateral circulation provides an alternative source of blood supply to myocardium jeopardised by ischaemia. Collaterals enlarge with obstructive coronary artery disease to allow bulk flow, but blood flow deliverable by the native, pre-formed collateral extent can already be sizeable. Genetic determinants contribute significantly to the wide variability observed in both native collateral extent and its capacity to enlarge, and the severity of the coronary stenosis is the most significant environmental determinant for collateral enlargement. The protective effect of a well-developed coronary collateral circulation translates into relevant improvements in all-cause and cardiac mortality in the acute and chronic phases of coronary artery disease, as well as into a reduction of future adverse cardiovascular events.

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Background. Clostridium difficile infection is one of the major causes of antibiotic associated diarrhea and colitis in the United States. Currently, there is a dearth of literature on the risk factors and outcomes differences between the patients with infection due to the hypervirulent strain vs. the non-hypervirulent strains. The objective of this study was to determine the relationship between C. difficile toxin type and clinical features, severity and outcome in patients with C. difficile diarrhea. ^ Methods. The case group included 37 patients who had infections due to hypervirulent strain (tcdC deletion) and the control group included 55 patients with other toxin types (toxin A, B, binary toxin). A univariate analysis was performed followed by a multivariable logistic regression analysis to assess the differences between cases and controls. ^ Results. In the multivariate analyses, we found out that being a male was a protective factor for developing the infection due to the hypervirulent strain [OR 0.33; 95% CI 0.12-0.90]. Also, the hypervirulent group has worse clinical and economic outcomes, although the differences were small and nonsignificant. ^ Conclusions. There may likely be no predictive risk factor for acquiring infection due to the hypervirulent strain and the acquisition may be more linked to the infection control practices of the individual hospitals or location of patients. Hence, better infection control practices may prove helpful in decreasing the overall disease burden and thus improve patient outcomes. ^

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Underwater spectral reflectance was measured for selected biotic and abiotic coral reef features of Glovers Reef, Belize from March 6 - 10, 2005. Spectral reflectance's of 63 different benthic types were obtained in-situ. An Ocean Optics USB2000 spectrometer was deployed in an custom made underwater housing with a 0.5 m fiber-optic probe mounted next to an artificial light source. Spectral readings were collected with the probe (bear fibre) about 5 cm from the target to ensure that the target would fill the field of view of the fiber optic (FOV diameter ~4.4 cm), as well as to reduce the attenuating effect of the intermediate water (Roelfsema et al., 2006). Spectral readings included for one target included: 1 reading of the covered spectral fibre to correct for instrument noise, 1 reading of spectralon panel mounted on divers wrist to measure incident ambient light, and 8 readings of the target. Spectral reflectance was calculated for each target by first subtracting the instrument noise reading from each other reading. The corrected target readings were then divided by the corrected spectralon reading resulting in spectral reflectance of each target reading. An average target spectral reflectance was calculated by averaging the eight individual spectral reflectance's of the target. If an individual target spectral reflectance was visual considered an outlier, it was not included in the average spectral reflectance calculation. See Roelfsema at al. (2006) for additional info on the methodology of underwater spectra collection.

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Subgrain boundaries revealed as shallow sublimation grooves on ice sample surfaces are a direct and easily observable feature of intracrystalline deformation and recrystallization. Statistical data obtained from the EPICA Dronning Maud Land (EDML) deep ice core drilled in East Antarctica cannot detect a depth region of increased subgrain-boundary formation. Grain-boundary morphologies show a strong influence of internal strain energy on the microstructure at all depths. The data do not support the classical view of a change of dominating recrystallization regimes with depth. Three major types of subgrain boundaries, reflecting high mechanical anisotropy, are specified in combination with crystal-orientation analysis.