SOCR News SpacekimeAnalytics Fall2019

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SOCR News & Events: Longitudinal Spacekime Analytics: Time Complexity & Inferential Uncertainty

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Title

Longitudinal Spacekime Analytics: Time Complexity & Inferential Uncertainty

Abstract

As Big biomedical and health data becomes more ubiquitous, the corresponding analytical challenges require novel techniques for data management, aggregation, harmonization, processing, and analytics. This talk will present a new technique for modeling high-dimensional and time-varying data. The Longitudinal Spacekime Analytics approach relies on extending the notions of time and event to complex-time (kime) and complex-event (kevent). We will illustrate how the kime-order (time) and kime-direction (phase) affect the subsequent predictive analytics and the induced scientific inference. We will present some of the mathematical foundations and reveal various statistical implications including inferential uncertainty and Bayesian formulation of spacekime analytics. Simulated data, clinical observations (e.g., fMRI, UK Biobank), and air quality data will be used to demonstrate applications of spacekime analytics.

Slidedeck

Presentation Slides (PDF).

SOCR Resources

SOCR Demos


References

R01CA233487, as well as, NSF Grants 1916425, 1734853 and 1636840.




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