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EKATERINA GALKINA, SHWETA PURUSHE, AND GEORGES G. GRINSTEIN (1 University Ave, Lowell, MA)
Over 5 million people are currently living with Alzheimer’s disease (AD) in the US alone. The progression of the disease is characterized by several stages of decline with few patients reverting back to normal cognition. Each individual’s particular trajectory of decline is thought to be influenced by a combination of genetic and environmental risk factors: exposure to early-life as well as late-life accelerators. We present Weave as a open-source platform for visualizing between-person differences in patterns of dementia progression. Interaction, linked highlighting between the tools, quick filtering and subset reduction support exploratory discovery and hypothesis generation. Weave was used in a preliminary analysis of the National Alzheimer’s Coordinating Center’s clinical, multidimensional time-series dataset. A pipeline for investigating a large longitudinal dataset is presented which aims to identify trajectory classes (i.e. stable, slow, fast decline) and factors influencing variability. Tracking subtle changes in cognition may lead to a better understanding of healthcare cost management, caregiver burden reduction and provide aggressive interventions