Braden Soper

Nonstationary Multivariate Gaussian Processes for Electronic Health Records

2019 · arXiv (Cornell University)

We propose multivariate nonstationary Gaussian processes for jointly modeling multiple clinical variables, where the key parameters, length-scales, standard deviations and the correlations between the observed output, are all time dependent. We perform posterior inference via …

Budget Constrained Machine Learning for Early Prediction of Adverse Outcomes for COVID-19 Patients

2021 · Research Square

Abstract Background: Machine learning (ML) based risk stratification models of Electronic Health records (EHR) data may help to optimize treatment of COVID-19 patients, but are often limited by their lack of clinical interpretability and cost …