arXiv · cs.AI · 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) · 5 小时前模型评分39
FITTER：基于指南与多智能体的个性化运动处方框架
A Guideline-Grounded Multi-Agent Framework for Personalized Exercise Prescription from Clinical and Wearable Data
导读
研究团队开发了 FITTER 多智能体框架，将临床与可穿戴数据同疾病特异性指南结合，生成个性化 FITT-VP 运动处方，并用确定性安全审计与修复纠正可规则校验的违规。在 400 名 All of Us 参与者数据上，其安全约束合规率达 98.5%，高于五个 大语言模型（LLM，Large Language Model） 对照组的 75.8%-85.8%，剂量精度与指南一致性也更优。
分类置信度
中 · 待人工复核
- 只有单一媒体来源，需要人工复核。
来源级别：媒体与个人
应用领域：医疗与生命科学
事件类型：研究发布
证据摘录
- “We developed FITTER, a multi-agent framework that integrates these data with condition-specific guidance to generate personalized FITT-VP prescriptions and applies deterministic safety audit and repair to correct rule-checkable violations.”
来源：arXiv · cs.AI · arxiv.org