The University of Wisconsin-Madison Prevention Research Center was recently awarded funding from the Centers for Disease Control and Prevention to conduct a Special Interest Project (SIP) focused on detecting early-stage ovarian cancer. The SIP is led by Drs. Irene Ong and Manish Patankar. In collaboration with Dr. Jesus Gonzalez from the University of Iowa and Dr. Peter Agenta from the University of Minnesota, the project will examine electronic health record data from three Midwestern health care systems using interpretable machine learning models to determine whether demographic/clinical variables, social determinants of health, and high-frequency germline genetic variants can be used to identify early predictors of ovarian cancer. The goal of the project is to develop novel computational tools identifying early-stage ovarian cancer and improve the long-term survival of patients and chances for cure. The researchers expect that such a predictive model will be especially useful for early detection of ovarian cancer in underrepresented and under-resourced women, and contribute to more equitable health care and health outcomes.