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PIKS: A Technique to Identify Actionable Trends for Policy-Makers Through Open Healthcare Data
We provide a comparison of our technique with three other existing outlier detection techniques, consisting of auto-encoders, isolation forests and feature bagging.
Building predictive models of healthcare costs with open healthcare data
We built models to predict costs from patient diagnoses and demographics.
A system for exploring big data: an iterative k-means searchlight for outlier detection on open health data
There may be hidden trends and patterns in the data that are worthy of further exploration and analysis.
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