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Diagnosis and Prognosis Using Machine Learning Trained on Brain Morphometry and White Matter Connectomes
[article]
2018
bioRxiv
pre-print
Accurate, reliable prediction of risk for Alzheimer's disease (AD) is essential for early, disease-modifying therapeutics. Multimodal MRI, such as structural and diffusion MRI, may contain multi-dimensional information neurodegenerative processes in AD. Here we tested the utility of structural MRI and diffusion MRI as imaging markers of AD using high-throughput brain phenotyping including morphometry and white-matter structural connectome (whole-brain tractography), and machine learning
doi:10.1101/255141
fatcat:cfvsbvqmxnf27keulvxyt5d6pm