Berkeley IEOR professor Ying Cui was recently awarded an R01 grant from the National Institutes of Health (NIH)’s National Cancer Institute, titled “SCH: A New Computational Framework for Learning from Imbalanced Biomedical Data,” for her work aimed at developing new machine learning tools to address the challenge of learning from imbalanced biomedical data, setting the stage for a better understanding of the increased risk of cardiovascular disease among breast cancer survivors.
Although remarkable advancements in prevention, diagnosis, and treatment have significantly increased survival rates for those with breast cancer, this progress is paralleled by a rise in cardiovascular disease among breast cancer survivors. Cardiovascular disease risk prediction models draw on imbalanced health record data from the broader population, showing an uneven distribution of cardiovascular disease outcomes among breast cancer survivors and no consistent pattern regarding when these cardiovascular complications might arise after the initial breast cancer diagnosis.
Under this NIH R01 grant, Berkeley IEOR Professor Ying Cui will collaborate closely with the University of Minnesota’s Ju Sun, an Assistant Professor in the Department of Computer Science & Engineering, and Rui Zhang, the Founding Chief of the Division of Computational Health Sciences and Associate Professor in the Department of Surgery. Together, this multidisciplinary team will develop predictive tools for learning from imbalanced data, with a specific focus on anticipating cardiovascular disease outcomes among breast cancer survivors. Through this pioneering effort, computational and theoretical foundations will contribute to improved learning from imbalanced data in healthcare contexts, laying the groundwork for more effective care and treatment strategies for breast cancer survivors.