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Automated Real-Time Surveillance Using Health Indicator Data Received at Different Time Intervals
Content Type: Abstract
The Johns Hopkins Applied Physics Laboratory and the Armed Forces Health Surveillance Center have developed a hybrid processing engine that alerts monitors when a severe health condition exists based on corroboration among several sources of data.… read more