Multivariate Time Series Analysis of Physiological and Clinical Data

Start: Wednesday, September 23, 2009, 02:00PM

End: Wednesday, September 23, 2009, 03:00PM

Location: ITE 325 B

Abstract: 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.

Host: Tim Finin


	UMBC eBiquity Events / Talks Multivariate Time Series Analysis of Physiological and Clinical Data OWL metadata Update record		Multivariate Time Series Analysis of Physiological and Clinical Data Tweet Speaker: Patti Ordonez Start: Wednesday, September 23, 2009, 02:00PM End: Wednesday, September 23, 2009, 03:00PM Location: ITE 325 B Abstract: 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. Host: Tim Finin ,