Novel research supported by NCI could lead to more specific predictive disease models.
A team of Stony Brook University researchers — led by two scientists in the Department of Biomedical Informatics in the Renaissance School of Medicine (RSOM) and College of Engineering and Applied Sciences (CEAS) — is developing a new way to analyze breast cancer imaging that incorporates mathematical modeling and deep learning. The approach will be much more interpretable and robust compared to previous methods. Their goal is to improve disease diagnosis and chart a treatment plan specific to the biomarker imaging and modeling findings.