# A Guideline-Grounded Multi-Agent Framework for Personalized Exercise Prescription from Clinical and Wearable Data

**Published:** November 4, 2026
**Author:** Xintong Li (Center for Data Science, Nell Hodgson Woodruff School of Nursing, Emory University, Department of Computer Science, Emory University), Yufen Lin (Nell Hodgson Woodruff School of Nursing, Emory University, Cancer Prevention and Control Research Program, Winship Cancer Institute, Emory University), Yuhua Wu (Center for Data Science, Nell Hodgson Woodruff School of Nursing, Emory University), Fengran Wang (Center for Data Science, Nell Hodgson Woodruff School of Nursing, Emory University), Minxiao Wang (Center for Data Science, Nell Hodgson Woodruff School of Nursing, Emory University), Rebecca A. Gary (Nell Hodgson Woodruff School of Nursing, Emory University), Jacob Kariuki (Lillian Carter Center for Global Health and Social Responsibility, Nell Hodgson Woodruff School of Nursing, Emory University), James Smith (Lancaster Medical School, Lancaster University), Sandra A. Billinger (Department of Neurology, University of Kansas Medical Center), Canhua Xiao (Nell Hodgson Woodruff School of Nursing, Emory University), Xiao Hu (Center for Data Science, Nell Hodgson Woodruff School of Nursing, Emory University, Department of Computer Science, Emory University, Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University), Runze Yan (Center for Data Science, Nell Hodgson Woodruff School of Nursing, Emory University)
**Source:** arXiv — cs.AI
**Language:** en-US
**HTML:** https://aiqazaqstan.com/en/articles/a-guideline-grounded-multi-agent-framework-for-personalized-exercise-pre

arXiv:2611.03983v1 Announce Type: new Abstract: Translating population-level exercise guidance into individualized prescriptions requires integrating clinical and wearable data, including diagnoses, medications, functional limitations, and baseline activity, with…

> From the original source: **arXiv — cs.AI**
> [Read full article at arXiv — cs.AI](https://arxiv.org/abs/2611.03983)

**Tags:** #arXiv

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