Code Blue events, which include cardiac or respiratory arrest, can be difficult to anticipate, researchers said.
Doctors use a scorecard, known as the Modified Early Warning Score, to estimate the severity of a patient's status by looking at vital signs like heart rate, blood pressure and temperature.
Sriram Somanchi of Carnegie Mellon University in Pittsburgh, Pennsylvania, and his colleagues wanted to see if a computer could predict when these emergencies were imminent.
The researchers trained a machine-learning algorithm on data from 133,000 patients who visited the NorthShore University HealthSystem, a partnership of four Chicago hospitals, between 2006 and 2011, 'New Scientist' reported.
Doctors called a Code Blue 815 times. By looking at 72 parameters in patients' medical history including vital signs, age, blood glucose and platelet counts, the system was able to tell, sometimes from data from four hours before an event, whether a patient would have gone into arrest.
It guessed correctly about two-thirds of the time, while a scorecard flagged just 30 percent of events.
The algorithm still needs work it reports a false positive 20 percent of the time, said Somanchi.
To improve its performance, his team is planning to train the system with data from other hospitals.

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