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A0836
Title: Investigating resting-state fMRI for Alzheimer's disease identification through functional data analysis Authors:  Ido Ji - Chungnam national university (Korea, South) [presenting]
Eunjee Lee - Chungnam National University (Korea, South)
Abstract: Alzheimer's disease (AD) is a debilitating neurodegenerative disorder affecting millions worldwide. Early detection and accurate diagnosis of AD are crucial for effective intervention and disease management. The potential of functional data analysis (FDA) is investigated using blood oxygenation level-dependent (BOLD) signals from resting-state functional magnetic resonance imaging (rs-fMRI) for the classification of Alzheimer's disease patients and healthy controls, as well as exploring brain regions associated with AD progression. Since FDA provides a powerful framework for analyzing complex biological signals, the methods were applied to extract relevant features from rs-fMRI and employed for classification purposes. The results demonstrate the effectiveness of the FDA in AD research using rs-fMRI data and, more importantly, reveal brain regions that may play a significant role in AD progression. This discovery could shed light on new neural mechanisms underlying AD and has potential implications for early diagnosis and targeted interventions.