Predicting Alzheimer’s Cognitive Resilience Score: A Comparative Study of Machine Learning Models Using RNA-seq Data
Akihiro Kitani,
Yusuke Matsui
Abstract:Alzheimer’s disease (AD) is an important research topic. While amyloid plaques and neurofibrillary tangles are hallmark pathological features of AD, cognitive resilience (CR) is a phenomenon where cognitive function remains preserved despite the presence of these pathological features. This study aimed to construct and compare predictive machine learning models for CR scores using RNA-seq data from the Religious Orders Study and Memory and Aging Project (ROSMAP) and Mount Sinai Brain Bank (MSBB) cohorts. We ev… Show more
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