The project has collected a large set of data (>200GB) from a cryptocurrency block chain. It is developing methods for detecting anomalies in transactions based on newer Social Networks, Graph Analysis and Machine Learning methods. The work involves data cleaning/wrangling and creation and implementation of various algorithms and analyzing the transactions for identifying different set of anomalies and manipulations.

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Alzheimer’s disease and related dementia (AD/dementia) represent a looming public health crisis, affecting roughly 5 million people in the U.S. and 11% of older adults. As with other chronic conditions, racial/ethnic and socio-economic disparities exist in the prevalence and burden of illness. However, less is known about how disparities in access to care influence the care trajectories – i.e., the scope, frequency and sequence of services used across healthcare settings – of those with AD/dementia.

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