This research will develop, implement, and evaluate an artificial intelligence-enabled workflow that would allow for online reading and same-day diagnostic imaging following screening mammography in breast cancer screening clinics.
This research will develop and evaluate a COMputerized PAtient-centered Collaborative Technology (COMPACT) to support personalized breast cancer decision making.
This research will examine the factors affecting cancer patients’ use of an electronic patient safety event reporting system to communicate adverse medication-related events to their care team.
This study will integrate a previously piloted risk tool and clinical decision aid, MammoScreen, with an EHR to provide personalized decision support for both patients and clinicians to improve quality of care for women who are at increased risk for breast cancer.
This research aims to adapt a decision support tool that integrates clinical risk information with patient preferences. The goal of this work is to support patients in making informed breast reconstruction decisions together with their clinicians.
