Breast cancer is one of the most common and deadliest cancers that affect mainly women
worldwide, and mammography examination is one of the main tools to help early detection …

Since 1948, Shannon theoretic methods for modeling information have found a wide range
of applications in several areas where information plays a key role, which goes well beyond …

We study the problem of discovering functional dependencies (FD) from a noisy data set. We
adopt a statistical perspective and draw connections between FD discovery and structure …

Background Clinical workflow is infused with large quantities of data, particularly in areas
with enhanced monitoring such as the Intensive Care Unit (ICU). Information theory can …

Electronic health records (EHRs) represent an underused data source that has great
research and clinical potential. Our goal was to quantify the value of EHRs in breast cancer …

Correct mammography evaluation demands great expertise and rigorous interpretation of
some radiographic features. The Breast Imaging Reporting and Data System (BI-RADS) is …

Predicting breast cancer risk has long been a goal of medical research in the pursuit of
precision medicine. The goal of this study is to develop novel penalized methods to improve …

Traditionally, patients with newly diagnosed invasive breast cancer underwent axillary US to
assess for suspicious axillary lymph nodes (LNs), which were then targeted for image …

Rationale and Objectives The discovery of germline genetic variants associated with breast
cancer has engendered interest in risk stratification for improved, targeted detection and …

Improved prediction of the “most harmful” breast cancers that cause the most substantive
morbidity and mortality would enable physicians to target more intense screening and …