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A sensitivity analysis to quantify the impact of neuroimaging preprocessing strategies on subsequent statistical analyses
Even though novel imaging techniques have been successful in studying brain structure and function, the measured biological signals are often contaminated by multiple sources of noise, arising due to e. g. head movements of the individual being scanned, limited spatial/temporal resolution, or other issues specific to each imaging technology.
Machine learning of neuroimaging to diagnose cognitive impairment and dementia: a systematic review and comparative analysis
METHODS: We systematically reviewed the literature, 2006 to late 2016, for machine learning studies differentiating healthy ageing through to dementia of various types, assessing study quality, and comparing accuracy at different disease boundaries.
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