In Pursuit of Better Data Forecasting
Yao Xie is aiming to create higher confidence in the data models that drive societal outcomes
New NSF-funded research advocates for the use of machine learning to go beyond standard point process data that classifies events at certain points in time. Using a neural network’s advantage in efficiency and ability to parse larger amounts of data, researchers are able to look at non-stationary data – like blood pressure, heart rate, or temperature in a patient – to model more potential outcomes at higher levels of confidence.