基于网络转移熵的复杂疾病预警信号

Rui Liu, Luonan Chen, K. Aihara
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引用次数: 0

摘要

许多证据表明,在复杂疾病的进展过程中,恶化通常不是平稳的,而是突然的,这可能导致从一种状态到另一种状态的关键转变,在一个临界点上,对应于潜在生物体的动力系统的分支。在达到正常状态和疾病状态之间的临界点之前,假定存在病前状态。由于病前状态被定义为正常状态的极限,代表疾病的早期预警信号,因此识别这种状态以便执行补救措施以避免突然过渡到疾病状态至关重要。尽管大多数复杂疾病没有模型,而且由于临床限制,通常只有小样本可用,但我们提出一个称为网络过渡熵(NTE)的指标可以作为预测临界过渡的预警指标。虽然理论偏差是基于动态网络生物标志物(DNB),但NTE的应用是DNB自由的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The early warning signal of complex diseases based on the network transition entropy
Many evidences suggested that during the progression of complex diseases, the deteriorations are generally not smooth but abrupt, which may cause a critical transition from one state to another at a tipping point, corresponding to a bifurcation of the dynamical system for the underlying organism. A pre-disease state is assumed to exist before reaching the tipping point between a normal state and a disease state. Since the predisease state is defined as a limit of the normal state, which represents an early-warning signal of the disease, it is crucial to identify such a state so that remedial actions can be executed to avoid the abrupt transition to the disease state. Although most complex diseases are model free, and usually only small samples are available due to clinical limitations, we propose that an index called the network transition entropy (NTE) may serving as an early-warning indicator for predicting the critical transition. Although the theoretical deviation is based on the dynamical network biomarker (DNB), the application of NTE is DNB free.
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