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Part of Special Issue " Spatial prediction modeling in natural hazards and risk " Abstract. The predictive power of logistic regression, support vector machines and bootstrap-aggregated classification trees (bagging, double-bagging) is compared using misclas-sification error rates on independent test data sets. Based on a resampling approach that takes into(More)
OBJECTIVE The aim of this study was to evaluate the longitudinal reproducibility of cartilage volume and surface area measurements in moderate osteoarthritis (OA) of the knee. MATERIALS AND METHODS We analysed 5 MRI (GE 1.5T, sagittal 3D SPGR) data sets of patients with osteoarthritis (OA) of the knee (Kellgren Lawrence grade I-II). Two scans were(More)
PURPOSE The aim of this analysis was to evaluate the diagnostic usefulness of frequency doubling technology (FDT) perimetry and short-wavelength perimetry (SWAP). Moreover, to study a combination of both methods using the machine-learning technique double-bagging, which was recently established in glaucoma research. METHODS Forty-three patients with(More)
PURPOSE This study was undertaken to characterize the influence of contrast, luminance, and spatial frequency of a pattern stimulus on the pupil reaction of healthy subjects. First measurements with this technique in patients with glaucoma were compared with those in a control group. METHOD Grating patterns were presented using a Maxwellian-view system to(More)
In recent years, social media emerged as a potential resource to improve the management of crisis situations such as disasters triggered by natural hazards. Although there is a growing research body concerned with the analysis of the usage of social media during disasters, most previous work has concentrated on using social media as a standalone information(More)
Clinical data from paired organs present a dependence structure that has to be considered when making statistical inference or evaluating classification rules with resampling-based techniques (bootstrap, cross-validation). We introduce a paired cross-validation approach for the estimation of misclassification error rates in the classification of data from(More)