Random forests have become a widely-used predictive model in many scientific disciplines within the past few years. Additionally, they are increasingly popular for assessing variable importance, e.g., in genetics and bioinformatics. We highlight both advantages and limitations of different variable importance scores and associated testing procedures, especially in the context of correlated pred...

OBJECTIVES Clinicians often base the implementation of therapies on the presence of postural instability in subjects with Parkinson's disease (PD). These decisions are frequently based on the pull test from the Unified Parkinson's Disease Rating Scale (UPDRS). We sought to determine whether combining the pull test, the one-leg stance test, the functional reach test, and UPDRS items 27-29 (arise...

Previous research has suggested that cerebral lesions observed on magnetic resonance imaging (MRI) of MS patients are clinically "silent." We examined the validity of this assertion by correlating neuropsychological test performance with MRI findings in 53 MS patients. We used a semiautomated quantitation system to measure three MRI variables: total lesion area (TLA), ventricular-brain ratio (V...

A neural control strategy for nonlinear processes with time-variant time-delay is proposed in this paper. In this strategy, a dynamic neural network based nonlinear Smith predictor is constructed to compensate for the effect of time-delay of a class of nonlinear processes. An on-line optimizing controller is illustrated based on the neural Smith predictor. It is known that the performance of th...

In this paper, we consider regression models with a Hilbert-space-valued predictor and a scalar response, where the response depends on the predictor only through a finite number of projections. The linear subspace spanned by these projections is called the effective dimension reduction (EDR) space. To determine the dimensionality of the EDR space, we focus on the leading principal component sc...

BACKGROUND There is interest in noninvasive H pylori testing as a means of predicting diagnosis and determining management in dyspeptic patients. AIMS To assess the value of the 14C urea breath test as a predictor of peptic ulcer disease in patients presenting with dyspepsia. PATIENTS AND METHODS 327 consecutive patients referred for investigation of dyspepsia had a 14C urea breath test per...

New learning algorithms for an adaptive nonlinear forward predictor that is based on a pipelined recurrent neural network (PRNN) are presented. A computationally efficient gradient descent (GD) learning algorithm, together with a novel extended recursive least squares (ERLS) learning algorithm, are proposed. Simulation studies based on three speech signals that have been made public and are ava...

In this paper, the tightly coupled INS/GPS integration system using an INS error predictor is proposed for improving the filter estimation performance when fewer than four satellites are tracked. The suggested error predictor stores the estimated position error in case of tracking above four satellites and calculates the initial error components for prediction of Schuler position error when few...

OBJECTIVES To conduct a pilot study to evaluate the predictive value of the Montreal Cognitive Assessment test (MoCA) and a brief test of multiple object tracking (MOT) relative to other tests of cognition and attention in identifying at-risk older drivers, and to determine which combination of tests provided the best overall prediction. METHODS Forty-seven currently licensed drivers (58-95 y...