864 resultados para Feature selection algorithm


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Magdeburg, Univ., Fak. für Informatik, Diss., 2011

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Magdeburg, Univ., Fak. für Naturwiss., Diss., 2012

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Magdeburg, Univ., Fak. für Informatik, Diss., 2011

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Background: Several researchers seek methods for the selection of homogeneous groups of animals in experimental studies, a fact justified because homogeneity is an indispensable prerequisite for casualization of treatments. The lack of robust methods that comply with statistical and biological principles is the reason why researchers use empirical or subjective methods, influencing their results. Objective: To develop a multivariate statistical model for the selection of a homogeneous group of animals for experimental research and to elaborate a computational package to use it. Methods: The set of echocardiographic data of 115 male Wistar rats with supravalvular aortic stenosis (AoS) was used as an example of model development. Initially, the data were standardized, and became dimensionless. Then, the variance matrix of the set was submitted to principal components analysis (PCA), aiming at reducing the parametric space and at retaining the relevant variability. That technique established a new Cartesian system into which the animals were allocated, and finally the confidence region (ellipsoid) was built for the profile of the animals’ homogeneous responses. The animals located inside the ellipsoid were considered as belonging to the homogeneous batch; those outside the ellipsoid were considered spurious. Results: The PCA established eight descriptive axes that represented the accumulated variance of the data set in 88.71%. The allocation of the animals in the new system and the construction of the confidence region revealed six spurious animals as compared to the homogeneous batch of 109 animals. Conclusion: The biometric criterion presented proved to be effective, because it considers the animal as a whole, analyzing jointly all parameters measured, in addition to having a small discard rate.

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ERP, auditory virtual reality, dichotic listening, selective auditory attention, cocktail-party phenomenon, HRTF

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Background:Vascular remodeling, the dynamic dimensional change in face of stress, can assume different directions as well as magnitudes in atherosclerotic disease. Classical measurements rely on reference to segments at a distance, risking inappropriate comparison between dislike vessel portions.Objective:to explore a new method for quantifying vessel remodeling, based on the comparison between a given target segment and its inferred normal dimensions.Methods:Geometric parameters and plaque composition were determined in 67 patients using three-vessel intravascular ultrasound with virtual histology (IVUS-VH). Coronary vessel remodeling at cross-section (n = 27.639) and lesion (n = 618) levels was assessed using classical metrics and a novel analytic algorithm based on the fractional vessel remodeling index (FVRI), which quantifies the total change in arterial wall dimensions related to the estimated normal dimension of the vessel. A prediction model was built to estimate the normal dimension of the vessel for calculation of FVRI.Results:According to the new algorithm, “Ectatic” remodeling pattern was least common, “Complete compensatory” remodeling was present in approximately half of the instances, and “Negative” and “Incomplete compensatory” remodeling types were detected in the remaining. Compared to a traditional diagnostic scheme, FVRI-based classification seemed to better discriminate plaque composition by IVUS-VH.Conclusion:Quantitative assessment of coronary remodeling using target segment dimensions offers a promising approach to evaluate the vessel response to plaque growth/regression.

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AbstractBackground:Guidelines recommend that in suspected stable coronary artery disease (CAD), a clinical (non-invasive) evaluation should be performed before coronary angiography.Objective:We assessed the efficacy of patient selection for coronary angiography in suspected stable CAD.Methods:We prospectively selected consecutive patients without known CAD, referred to a high-volume tertiary center. Demographic characteristics, risk factors, symptoms and non-invasive test results were correlated to the presence of obstructive CAD. We estimated the CAD probability based on available clinical data and the incremental diagnostic value of previous non-invasive tests.Results:A total of 830 patients were included; median age was 61 years, 49.3% were males, 81% had hypertension and 35.5% were diabetics. Non-invasive tests were performed in 64.8% of the patients. At coronary angiography, 23.8% of the patients had obstructive CAD. The independent predictors for obstructive CAD were: male gender (odds ratio [OR], 3.95; confidence interval [CI] 95%, 2.70 - 5.77), age (OR for 5 years increment, 1.15; CI 95%, 1.06 - 1.26), diabetes (OR, 2.01; CI 95%, 1.40 - 2.90), dyslipidemia (OR, 2.02; CI 95%, 1.32 - 3.07), typical angina (OR, 2.92; CI 95%, 1.77 - 4.83) and previous non-invasive test (OR 1.54; CI 95% 1.05 - 2.27).Conclusions:In this study, less than a quarter of the patients referred for coronary angiography with suspected CAD had the diagnosis confirmed. A better clinical and non-invasive assessment is necessary, to improve the efficacy of patient selection for coronary angiography.