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Multimodal neuroimaging biomarkers for early detection of frontotemporal dementia using machine learning and large-scale multisite longitudinal datasets

PI: Wang

Summary:
We propose to use machine learning to develop multimodal neuroimaging biomarkers for early detection and monitoring progression of FTD, using neuroimaging data, clinical severity, and cognitive assessments provided by multiple consortium efforts on FTD research, while capitalizing on unique opportunities for collecting new imaging data to further increase sample size.