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穆罕默德·本·扎耶德人工智能大学 数字生物统计学 Marcos Matabuena 研究组

用于追踪肌萎缩侧索硬化症进展的函数型分布生物标志物

In this project, we develop novel statistical methods to exploit near-continuous measurements of hand movements collected from individuals with amyotrophic lateral sclerosis (ALS) over a two-year longitudinal study.

Our goal is to construct functional and distributional biomarkers that improve the monitoring of disease progression and enable more accurate prediction of survival.

By capturing subtle changes in movement patterns over time, these methods aim to provide richer and more sensitive measures of disease evolution than conventional clinical metrics, ultimately supporting earlier detection of deterioration and more precise evaluation of ALS progression.