Title: NSF CAREER Award Supports Development of Machine Learning Tools for Preeclampsia Detection
Assistant Professor Talayeh Razzaghi from the University of Oklahoma has been honored with a prestigious NSF CAREER award to propel her research in creating machine learning-based tools for early detection of preeclampsia in maternal healthcare.
Preeclampsia, a serious pregnancy complication characterized by high blood pressure, affects a significant percentage of pregnancies in the U.S. annually, posing risks to both maternal and neonatal health if left untreated. The issue lies in the challenge of identifying women at higher risk for developing preeclampsia due to factors such as age, race, and pre-pregnancy health conditions.
Razzaghi’s research aims to tackle these challenges head-on by utilizing advanced machine learning algorithms to analyze diverse datasets and predict the likelihood of preeclampsia during pregnancy, with a particular focus on underserved minority populations. By addressing biases present in existing predictive models, which often neglect the specific healthcare needs of communities of color, this research strives to enhance the early identification of pregnant women at risk of developing preeclampsia while promoting fairness in maternal health management systems.
The implications of this research extend beyond preeclampsia detection. By understanding and addressing the intricate interplay of social determinants of health, insights gained from this study can be applied to other pregnancy-related diseases and non-clinical factors like socioeconomic status.
With collaborations with clinical partners at prestigious institutions like the OU Health Sciences Center, Texas Tech Health Sciences Center, and the University of Pittsburgh, Razzaghi has access to crucial datasets necessary for training and validating machine learning models. However, she acknowledges the challenges associated with accessing sensitive healthcare data and highlights the importance of ethically sound data usage and privacy protection.
This research not only aims to advance scientific knowledge and enhance healthcare outcomes but also emphasizes the significance of respecting patient privacy and confidentiality throughout the process. Additionally, through a focus on a recruitment and research internship program that includes underrepresented students in STEM, Razzaghi’s CAREER award will work towards promoting diversity in the field.
By combining cutting-edge technology with a deep commitment to ethical standards, Talayeh Razzaghi’s NSF CAREER award project will not only contribute to the field of maternal healthcare but also pave the way for more equitable and personalized healthcare solutions for all individuals, regardless of background or circumstances.
