A machine learning model identifies environmental and social risk factors that contribute to these cardiac events.
A machine learning model identifies environmental and social risk factors that contribute to these cardiac events.
Out-of-hospital cardiac arrest, or OHCA, is a leading cause of mortality worldwide and 90% of cases are fatal.
Patients lose cardiac function and circulation, and every minute they remain untreated decreases the likelihood of a good outcome.
In a study published in npj Digital Medicine, a team of researchers led by the University of Michigan developed a machine learning model that identified 17 environmental and social factors that can influence the risk of OHCA.
Read More: University of Michigan
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