News and Analysis

Researchers at the US Department of Energy’s Oak Ridge National Laboratory are using a mathematical technique called differential privacy to gain insights from personal health data, without compromising patient privacy. As the technique reduces data set accuracy, the researchers are combining methods from the differential privacy and machine learning communities to improve their model’s performance. The team aims to have its method widely used in the medical community within three years.