The University of Wisconsin, in a partnership with the Morgridge Institute for Research and the Marshfield Clinic Research Foundation, has received a grant from the National Institutes of Health (NIH) to establish the Center for Predictive Computational Phenotyping (CPCP), as one of NIH’s new Centers of Excellence for Big Data Computing in the Biomedical Sciences. The grant will provide nearly $11 million over a four-year period.
While there are many projects underway at the CPCP, including studies on heart attacks and blood clots, UW Radiology is chiefly involved with investigating breast cancer.
Representing UW Radiology is Dr. Beth Burnside, the only clinician acting as a primary investigator on the project. Her team, led by Yirong Wu, Ph.D., will use computational modeling to predict the likely phenotype of future breast cancer based on known and newly discovered demographic, genetic, and imaging risk factors.
This predictive phenotyping is designed to inform the optimal use of breast cancer screening modalities such as digital mammography and ultrasound in a personalized manner. Tailoring the imaging method to the individual patient can allow clinicians to proactively detect and diagnose meaningful cancers (those that cause morbidity and mortality), while limiting testing that is unnecessary or will increase false positives and overdiagnosis.
The Center for Predictive Computational Phenotyping (CPCP) is one of 11 NIH Centers of Excellence intended to accelerate the impact of predictive modeling on clinical practice. The CPCP will focus on issues related to computational phenotyping and produce disease prediction models from machine learning and statistical methods. These models will integrate data from electronic health records, images, molecular profiles and other datasets to predict patient risks for breast cancer, heart attacks and severe blood clots. Project PIs come from a wide array of disciplines including engineering, bioinformatics, statistics, computer science, and radiology.