阿尔茨海默病的适应性亚型和分期推断。

Xinkai Wang, Yonggang Shi
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引用次数: 0

摘要

亚型和阶段推断(SuStaIn)是一种有用的基于事件的模型,用于捕获任何进行性疾病的时间和表型模式,这对于理解此类疾病的异质性至关重要。然而,该模型不能捕获具有不同进展率的亚型,相对于预定义的生物标志物,在推理之前具有固定的事件。因此,我们提出了一种自适应算法,用于在进行子类型和阶段推理的同时学习特定于子类型的事件。我们使用模拟来演示有关各种性能指标的改进。最后,我们提供了阿尔茨海默病(AD)数据中不同亚型中不同水平的生物标志物异常的快照,以证明我们的算法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Adaptive Subtype and Stage Inference for Alzheimer's Disease.

Subtype and Stage Inference (SuStaIn) is a useful Event-based Model for capturing both the temporal and the phenotypical patterns for any progressive disorders, which is essential for understanding the heterogeneous nature of such diseases. However, this model cannot capture subtypes with different progression rates with respect to predefined biomarkers with fixed events prior to inference. Therefore, we propose an adaptive algorithm for learning subtype-specific events while making subtype and stage inference. We use simulation to demonstrate the improvement with respect to various performance metrics. Finally, we provide snapshots of different levels of biomarker abnormality within different subtypes on Alzheimer's Disease (AD) data to demonstrate the effectiveness of our algorithm.

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