OBJECTIVE The aim of this study was to compare screening performance for Down syndrome of the absolute risk (AR) method to the first trimester combined test (FCT) at different maternal ages. METHODS There was a retrospective analysis of 32,448 FCT. AR was defined as final risk divided by maternal age risk. RESULTS The likelihood of receiving a true prediction was comparable between both met...

July-August 2012 Imagine you fly home from vacation with your one-and-ahalf-year-old son who is traveling for free as a “lap child.” In the airport parking lot, you put him into his forwardfacing car seat, where he sits much more contentedly than he did in the rear-facing one that was mandatory until his first birthday. After he falls asleep on the way home, you transfer him to his crib without...

In an increasing number of applications, it is of interest to recover an approximately low-rank data matrix from noisy observations. This paper develops an unbiased risk estimate—holding in a Gaussian model—for any spectral estimator obeying some mild regularity assumptions. In particular, we give an unbiased risk estimate formula for singular value thresholding (SVT), a popular estimation stra...

We study the degrees of freedom of the Lasso in the framework of Stein’s unbiased risk estimation (SURE). We show that the number of non-zero coefficients is an unbiased estimate for the degrees of freedom of the Lasso—a conclusion that requires no special assumption on the predictors. Our analysis also provides mathematical support for a related conjecture by Efron et al. (2004). As an applica...

Shrinkage preliminary test estimation in exponential distribution under a precautionary loss function is considered. The minimum risk-unbiased estimator is derived and some shrinkage preliminary test estimators are proposed. We apply our results on censored data and records. The relative efficiencies of proposed estimators with respect to the minimum ‎risk-unbiased‎&...

This paper is devoted to adaptive signal denoising in the context of Graph Signal Processing (GSP) using Spectral Wavelet Transform (SGWT). issue addressed via a data-driven thresholding process transformed domain by optimizing parameters sense Mean Square Error (MSE) Stein’s Unbiased Risk Estimator (SURE). The SGWT considered built upon partition unity making transform semi-orthogonal so that ...

Some examples of absurd uniformly minimum variance unbiased estimators are discussed. Two reasons, argued in the literature, for having such estimators are lack of enough information in the available data and property of unbiasedness. In this paper, accepting both of these views, we show that an appropriate choice of loss function using a general concept of unbiasedness leads to risk unb...

BACKGROUND Uncertainty exists about the performance of the Framingham risk score when applied in different populations. OBJECTIVE We assessed calibration of the Framingham risk score (ie, relationship between predicted and observed coronary event rates) in US and non-US populations free of cardiovascular disease. METHODS We reviewed studies that evaluated the performance of the Framingham r...

Recent deep learning based denoisers are trained to minimize the mean squared error (MSE) between the output of a network and the ground truth noiseless image in the training data. Thus, it is crucial to have high quality noiseless training data for high performance denoisers. Unfortunately, in some application areas such as medical imaging, it is expensive or even infeasible to acquire such a ...