Evolving Characteristics of Gadolinium-Based Contrast Agents for MR Imaging: A Systematic Review of the Importance of Relaxivity.

Gadolinium-based contrast agents (GBCAs) are widely and routinely used to enhance the diagnostic performance of magnetic resonance imaging and magnetic resonance angiography examinations. T1 relaxivity (r) is the measure of their ability to increase signal intensity in tissues and blood on T1-weighted images at a given dose. Pharmaceutical companies have invested in the design and development of GBCAs with higher and higher T1 relaxivity values, and "high relaxivity" is a claim frequently used to promote GBCAs, with no clear definition of what "high relaxivity" means, or general concurrence about its clinical benefit.

EHR-Safe: generating high-fidelity and privacy-preserving synthetic electronic health records.

Privacy concerns often arise as the key bottleneck for the sharing of data between consumers and data holders, particularly for sensitive data such as Electronic Health Records (EHR). This impedes the application of data analytics and ML-based innovations with tremendous potential. One promising approach for such privacy concerns is to instead use synthetic data.

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States.

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.