University of Miami to Build AI Platform for Breast Cancer Survivorship

The University of Miami’s Sylvester Comprehensive Cancer Center has received an award from the Breast Cancer Research Foundation (BCRF) to develop an artificial intelligence platform dedicated to breast cancer survivorship. The initiative aims to bridge the gap in long-term care by using AI to enhance care coordination and patient quality of life.

Led by Dr. Frank J. Penedo, director of Sylvester’s Survivorship and Supportive Care Institute, the project will focus on the creation of a platform called "My Wellness Support." This AI-powered tool is designed to identify unmet supportive care needs and deliver personalized guidance to patients during the intervals between their scheduled clinic visits.

The Challenge of Survivorship

Breast cancer survivorship care requires the long-term management of both the physical and psychological effects that persist after primary treatments like surgery, chemotherapy, or radiation. Historically, this phase of care has relied on periodic appointments, which can leave gaps in monitoring and support. As the population of survivors grows, healthcare systems are increasingly exploring AI to personalize follow-up care and identify high-risk patients more efficiently than traditional manual screening.

Impact on Patient Care

Integrating AI into survivorship care has the potential to significantly reduce the administrative and clinical burden on healthcare providers. By automating the identification of patient needs, the "My Wellness Support" platform can ensure that survivors receive timely, personalized interventions. This proactive approach is critical for managing long-term side effects and implementing strategies to prevent cancer recurrence, ultimately shifting care from a reactive model to a preventative one.

Future Outlook

As the University of Miami begins the development of the platform, the medical community will be watching how AI-driven guidance affects patient adherence and overall health outcomes. While the project focuses on the technical deployment of the AI, the long-term success of the initiative will depend on how effectively the tool integrates into existing clinical workflows and the degree to which it can accurately predict patient needs in real-time. This shift toward AI-driven monitoring represents a broader trend in oncology to move beyond the clinic walls, ensuring that the transition from active treatment to long-term survivorship is seamless and data-driven.