Multivariate Conditional Outlier Detection and Its Clinical Application

Hong, Charmgil (University of Pittsburgh) | Hauskrecht, Milos (University of Pittsburgh)

AAAI Conferences 

Over the past decades, the quality of healthcare and its improvement have been the center pieces of many public In the first fold, our key objective is to accurately and efficiently programs and initiatives. Recent studies on patient safety, learn a compact representation of complex clinical however, revealed that preventable medical errors are more records. For clinical data, this is particularly challenging widespread than initially thought, which are now estimated because each record may contain hundreds to thousands to be one of the leading causes of death (James 2013).

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