]> 2009-09-23T14:00:00-05:00 2009-09-23T15:00:00-05:00 Patricia Ordóñez Rozo will talk abut her PhD research

Multivariate Time Series Amalgams (MTSAs) provide an integrated, multivariate approach to representing clinical and physiological data. The hybrid representation automates the personalization of baselines and thresholds based on a patient’s medical history while also incorporating traditional baselines and thresholds. The visualization of this representation captures the rate of change of provider-selected parameters and the relationships among them. It groups parameters according to their influence on four vital organs: the heart, lung, kidney, and liver. A novel similarity metric for this representation, inspired by wavelets and Symbolic Aggregate Approximation (SAX), is the cornerstone to the development of a search engine for large medical databases. ]]>