面向阿尔茨海默病精准医学的物理信息多尺度数字孪生研究
Towards a physics-informed multiscale digital twin for precision medicine in Alzheimer's disease
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中文总结 AI 辅助
针对阿尔茨海默病精准医学中大脑衰老与神经退行性变轨迹异质性的挑战，提出PIM-BrainTwin物理信息多尺度数字孪生联邦平台，量化残余代偿能力与系统稳定性，可形式化、比较与优化不同机制假设。
中文摘要 AI 辅助
解析大脑衰老与神经退行性变的驱动因素、解释个体轨迹异质性仍是精准医学的核心挑战。我们提出PIM-BrainTwin，一种面向阿尔茨海默病的物理信息多尺度数字孪生，借鉴材料科学原理（类疲劳耗竭、安全裕度与临界转变）量化残余代偿能力与系统稳定性。该平台为开放、模块化的联邦框架，可对不同机制假设进行形式化、比较与优化。
英文摘要
Deciphering the drivers of brain ageing and neurodegeneration, and explaining heterogeneity in individual trajectories, remains a central challenge for precision medicine. We propose PIM-BrainTwin, a physics-informed multiscale digital twin for Alzheimer's disease that draws on materials-science principles--fatigue-like depletion, safety margins and critical transitions--to quantify residual compensatory capacity and system stability. Designed as an open, modular and federated platform, it enables alternative mechanistic hypotheses to be formalised, compared and refined.
