The National Institutes of Health awarded $4 million to Memorial Sloan Kettering Cancer Center (MSKCC) and the City College of New York (CCNY) to study the use of machine learning for early breast cancer detection in high-risk women, reports MSKCC’s news organization. Led by Principal Investigator Elizabeth J. Sutton, a breast imaging specialist and Associate Members of MSKCC’s Department of Radiology, the group will investigate the power of machine learning to help analyze medical images to determine those individuals facing the greatest risk earlier on in the process. A key goal—limit the burden of screening on this vulnerable population. This collaborative is the result of an ongoing effort combining clinicians, engineers, and physicists from both MSKCC and CCNY.
As part of the study known as “Machine Learning for Risk-Adjusted Breast MRI Screening,” the teams will analyze 100,000 breast exams from MSKCC, Duke University and Johns Hopkins University as the investigational team believe the large data set affords opportunity to identify future risk these women face. A key goal—detect tumors earlier and help save lives!
Elizabeth J. Sutton, MD, Radiologist,
Lucas C. Parra, PhD, Professor, Harold Shames Chair and Professor of Biomedical Engineering, CCNY
Call to Action: Connect with these investigators to collaborate.