UMBC ebiquity
Multivariate Time Series Analysis of Physiological and Clinical Data
Wednesday, September 23, 2009, 14:00pm - Wednesday, September 23, 2009, 15:00pm
ITE 325 B
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.
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.