S22-043 Longitudinal risk assessment of neonatal morbidities in newborns utilizing artificial intelligence and electronic health records Stanford researchers have developed a method for assessing neonatal health risk by using longitudinal electronic health records (EHR) utilizing a machine learning model comprising deep learning neural networks. Davide De Franchesco Jonathan Reiss David Stevenson Nima Aghaeepour
S20-528 Risk Stratification in Newborns Based on Metabolites Using Deep Learning Prematurity is the single largest cause of death in children under 5 years of age, both in low-and high-income countries. Nima Aghaeepour Alan Chang Jonathan Reiss Gary Shaw Karl Sylvester David Stevenson Jonathan Mayo
S21-061 PREDICTION OF PREECLAMPSIA RISK USING CIRCULATING CELL-FREE RNA Researchers at Stanford and the Chan Zuckerberg Biohub have developed methods for predicting the risk or existence of preeclampsia. Stephen Quake Gary Shaw David Stevenson Mira Moufarrej
S00-048 Heme oxygenase transgenic reporter mouse (HO Luc Mouse) HO-1-luc 15 as a transgene in mice. Pamela Contag Christopher Contag David Stevenson