AI Platform Personalizes Support Between Visits for Cancer Survivors

Cancer survivors often manage persistent side effects after treatment, including fatigue, anxiety, uncertainty, symptoms, stress, and questions between appointments. Clinical teams need ways to maintain oversight while providing evidence-based support outside scheduled visits. In response, new findings demonstrate an AI framework designed to personalize survivorship and supportive care while preserving clinical safety guardrails.

Sylvester Comprehensive Cancer Center, part of the University of Miami Miller School of Medicine, has developed Precision AI for Survivorship and Supportive Care. The framework is intended to guide the development, evaluation and implementation of AI tools in cancer survivorship and supportive care. It supports an AI-enabled platform called My Wellness Support, which builds on data and infrastructure from My Wellness Check.

My Wellness Check is an electronic health record-integrated screening and triage program in which patients routinely report symptoms, quality-of-life concerns, practical needs and other survivorship challenges before appointments. The program has collected longitudinal patient-reported outcomes, supportive care needs and nutritional data from more than 37,000 ambulatory oncology patients. Researchers also evaluated data from a subsample of 25,592 ambulatory cancer survivors followed over 36 months to develop machine-learning models identifying patterns associated with symptom burden and unplanned health care use.

My Wellness Support combines patient-reported outcomes, clinical records and behavioral information to identify risk patterns and unmet needs. The platform uses that information to tailor evidence-based educational resources, symptom-management strategies, practical support resources and supportive care recommendations. Survivors interact with an AI companion, while the study team and clinicians monitor trends, risk scores and alerts through a dedicated dashboard.

Implementation of advanced analytic and AI-driven techniques improved predictive precision for unfavorable outcomes by more than 25%. The project remains in early testing and is designed to operate within established clinical guidelines and safety guardrails with human oversight. The proof-of-concept study was published in Translational Behavioral Medicine on September 25, 2026.

“New technologies often move faster than the systems designed to evaluate them. That's why our framework emphasizes scientific validation, transparency and continuous evaluation. If AI is going to become part of adjunctive survivorship and supportive care, we have to ensure it is safe, effective and developed with a range of patient populations in mind,” said Sara Fleszar-Pavlović, Ph.D., research assistant professor in the Miller School’s Division of Medical Oncology and director of research operations for Sylvester’s Survivorship and Supportive Care Institute.

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Sylvester Comprehensive Cancer Center