March 12, 2024, 4:43 a.m. | Qing Xiao, Siyeop Yoon, Hui Ren, Matthew Tivnan, Lichao Sun, Quanzheng Li, Tianming Liu, Yu Zhang, Xiang Li

cs.LG updates on arXiv.org arxiv.org

arXiv:2403.06940v1 Announce Type: cross
Abstract: Alzheimer's Disease (AD) is a neurodegenerative condition characterized by diverse progression rates among individuals, with changes in cortical thickness (CTh) closely linked to its progression. Accurately forecasting CTh trajectories can significantly enhance early diagnosis and intervention strategies, providing timely care. However, the longitudinal data essential for these studies often suffer from temporal sparsity and incompleteness, presenting substantial challenges in modeling the disease's progression accurately. Existing methods are limited, focusing primarily on datasets without missing entries …

abstract alzheimer's arxiv cs.lg data diagnosis diffusion diffusion model disease diverse eess.iv forecasting however prediction q-bio.qm strategies trajectory type

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