Early Diagnosis Algorithms for ICU Emergencies


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    The vital signs of patients in ICU are usually very unstable. This requires immediate assistance from medical personnel. Due to the limited resources, not all the emergencies were handled in time, leading to unexpected fatal outcomes. Most cases like these can be avoided, if they are predicted and the medical assistance is provided before the emergencies occur. Common emergencies include sudden death, septicemia, lung infection, acute hypotension, and organ failure. Current models based on the monitored physiological data can provide sensitive predictions for some emergency types. There are three types of commonly used data, i.e. static data, event data and time series data. The static data is easily obtained, but leads to less accurate predictions than the event data and time series data do. It is expected, that the interest for collecting and processing event data and time series data will grow in the near future.

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LI Kai-shi, FAN Jian-ping, ZHOU Feng-feng. Early Diagnosis Algorithms for ICU Emergencies[J]. Journal of Integration Technology,2012,1(2):13-19

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  • Online: November 20,2012
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