Data Competition | Event 2

Robust Algorithms across Sources, Inputs, and Noise

In Challenge Event 2, the data size will significantly increase in size. 

Additional data types will add to the training data’s complexity. To win a prize, teams’ performance must exceed the specified baseline algorithm as well as specificity, sensitivity and lead time thresholds.

Technical Challenge Elements

	Multiple Data Sources With varied source populations, patient demographics, types of injury, and standard clinical operating procedures. Each data set may have a different standard set of sensor readings, with different added sensors in each phase of the DARPA Triage Challenge. Approaches must demonstrate robustness across a range of datasets and sensor types.
	Multiple Data Inputs Includes static data (e.g., mechanism of injury or anatomical injury pattern); multiple simultaneous, continuous streams of high-frequency waveforms; and potentially point-of-care imaging data.
	Raw Data Data as it comes from the sensors (i.e., without any post-sensor cleaning), with the noise, aberrant values, and dropouts that occur in clinical environments.
	Degraded Data DARPA may inject additional challenges that can be expected in battlefield and civilian pre-hospital settings, such as noisy, aberrant values, severe degradation or total loss of a particular sensor, to test the robustness of competitor strategies to such plausible scenarios.