Our architecture has direct implications for multiple time-oriented tasks e.g., monitoring, early detection of clinically significant patterns, decision support regarding interpretations and the relevant appropriate actions, therapy planning, health-care policy formation, and data mining/knowledge discovery.

Our system exploits multiple insights developed over the past decade, regarding the nature of intelligent monitoring and query mediation, knowledge-based visualization, distributed knowledge acquisition, and distributed problem solving.

Our visualization tools support early detection and trend analysis. Our interactive exploration tools display connections and relations, both during the same time and over time, not only between raw data types, but also among clinically meaningful concepts (abstractions of the raw data) in a way that is currently unavailable.  Clients are able to visualize the aggregated patient data in new ways; e.g., to align and display the data using the advanced concept of “relative time” alignment, which aligns all data according to a clinically meaningful concept such as treatment date or surgery date.

Clients are able to display meaningful patterns over time in patient data; and in general, to perform comparisons and explorations that were not possible till now. 

All of the above capabilities enable clients to continue to provide world leading research and facilities to their patients.