arXiv 人工智能· 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)·· 6 小时前AI 评分36
基于临床与穿戴设备数据的多智能体个性化运动处方框架 FITTER
A Guideline-Grounded Multi-Agent Framework for Personalized Exercise Prescription from Clinical and Wearable Data
AI 导读
多智能体框架 FITTER 整合临床、穿戴设备数据与疾病指南，可生成个性化 FITT-VP 运动处方并执行确定性安全审计与修复。在 400 名参与者数据测试中，FITTER 的安全约束合规率达 98.5%，显著优于 5 款对比 LLM 的 75.8%–85.8%。消融实验证实安全审计与修复是高合规率的核心支撑，临床医生亦完成了 80 份处方的结构化评审。
来源：arXiv 人工智能 · arxiv.org