Oak Ridge Biosurveillance Toolkit (ORBiT)
ORNL has played a key role in developing novel Big Data toolkits in the context of syndromic disease surveillance. Our platform, the Oak Ridge Bio-surveillance Toolkit (ORBiT) enables large-scale analysis of heterogeneous data sources, including environmental, climate/weather related data, prescriptions records and other novel data streams emerging from social media (e.g., Twitter, Instagram). ORBiT is targeted at developing novel statistical and machine learning tools instead of acting as a central data collection interface from these heterogeneous resources. Additionally, it also provides an application programming interface (API) that can be used by end-users to target specific bio-surveillance applications. Machine learning tools are tightly integrated with visualization tools in a web-based framework to aid the end users or analysts in exploring potential links between heterogeneous data sets, detecting patterns/correlations across multiple data streams, identifying emerging disease outbreaks, forecasting emerging epidemics, and monitoring control strategies. ORBiT is implemented as a component-based, plug-and-play toolkit that exploits existing distributed cloud-based analytics frameworks.
Ramanathan, A., Laura Pullum, et al. “Discovering Multi-scale Co-occurrence Patterns of Asthma and Influenza with the Oak Ridge Bio-surveillance Toolkit.” Frontiers in Public Health 3, no. 1, 1-12, (2015).
Ramanathan, Arvind, Laura Pullum, et al. “ORBiT: Oak Ridge Bio-surveillance Toolkit for Public Health Dynamics.” BMC Bioinformatics 16, (2015).
Ramanathan, Arvind, Laura Pullum, et al. “Discovery of Disease Co-occurrence Patterns from Electronic Healthcare Reimbursement Claims Data.” In Knowledge Discovery and Data Mining Big Data in Health Informatics (KDD-BHI), 2014.
Ramanathan, Arvind, Pullum, Laura L, Steed, Chad A, Parker, Tara L, Quinn, Shannon P, & Chennubhotla, Chakra S. (2013). Oak Ridge Bio-surveillance Toolkit (ORBiT): Integrating Big-Data Analytics with Visual Analysis for Public Health Dynamics. In Public Health's Wicked Problems: Can InfoVis Save Lives? 2013.
Pullum, Laura, & Ramanathan, Arvind. ORBiT–The Oak Ridge Biosurveillance Toolkit. IDIS 2013.
Ramanathan, Arvind, Pullum, Laura L, Steed, Chad A, Quinn, Shannon S, Chennubhotla, Chakra S, & Parker, Tara. (2013). Integrating heterogeneous healthcare datasets and visual analytics for disease bio-surveillance and dynamics. IEEE Workshop on Interactive Visual Text Analytics (Atlanta, GA).