OU research using artificial intelligence to predict preeclampsia risk – IAM Network

NORMAN –Talayeh Razzaghi, an assistant professor in the School of Industrial and Systems Engineering, University of Oklahoma Gallogly College of Engineering, is leading a project using machine learning and artificial intelligence techniques to predict when pregnant women may have an increased risk of preeclampsia. "Preeclampsia is a subtype of hypertension (high blood pressure) developed during pregnancy that can lead to serious, even fatal, complications for both the mother and the fetus," Razzaghi said. "Our central hypothesis is that machine learning-based models can fundamentally transform clinicians' existing decision support tools for detection and monitoring preeclampsia for minority groups by addressing the key issues specific to preeclampsia datasets. This approach assists clinicians in the prognosis of adverse delivery outcomes. In particular, the research methodology in this study addresses biases and outcome health delivery disparities among Hispanic and Native populations in Oklahoma and Texas."The