A 2023 law championed by Republicans requires the CDC have a director confirmed by the Senate. For months, though, it's had only acting directors--and the White House won't say when that will change. As the agency rotates through a cast of leaders, it's unclear when--or if--the US Centers for Disease Control and Prevention will get a permanent director under Donald Trump's second term as president. Following Jim O'Neill's departure as acting CDC director last week, National Institutes of Health director Jay Bhattacharya will now lead both agencies temporarily. It's the latest in a series of shakeups at Trump's CDC, which has lost about a quarter of its staff to mass layoffs carried out by Health and Human Services Secretary Robert F. Kennedy, Jr. last year.

To fill this gap, we introduce a nonparametric causal inference framework for analyzing "closed-loop" designs, which use

We present an alternative approach to decompose non-negative tensors, called many-body approximation .

Before that, it is crucial to develop benchmarks to evaluate L VLMs' effectiveness in various medical applications.

Estimating the density of a distribution from samples is a fundamental problem in statistics. In many practical settings, the Wasserstein distance is an appropriate error metric for density estimation. For example, when estimating population densities in a geographic region, a small Wasserstein distance means that the estimate is able to capture roughly where the population mass is. In this work we study differentially private density estimation in the Wasserstein distance. We design and analyze instance-optimal algorithms for this problem that can adapt to easy instances.

Deidentification algorithms are vulnerable to the same bias and privacy issues that impact other data analytics and machine learning applications, and it can even amplify those issues by contaminating downstream applications.

Neural Information Processing Systems http://nips.cc/

M-SYNTH is organized into a directory structure that indicates the parameters. Code and dataset is released with the Creative Commons 1.0 Universal License We now review the timing required to perform mass insertion and imaging. In Table 2, we review the imaging time required for each breast density. The time varies from 2.84 GPU), we were able to generate the complete dataset in about two weeks.Breast Density Time (min) Fatty 13.463809 Scattered 11.002291 Hetero 3.655613 Dense 2.842028 Table 2: Timing analysis for imaging by breast density. Additional renderings of the breast phantoms generated for the study are shown in Figure 1, demonstrating a high level of detail and anatomical variability within and among models.