Machine learning helps predict survival rates of out-of-hospital cardiac arrest

November 18, 2020

DALLAS, TX — Using neighborhood and local data in combination with existing information sources creates a more accurate prediction on a patient’s recovery prospects after an out-of-hospital cardiac arrest (OHCA), according to preliminary research to be presented at the American Heart Association’s Resuscitation Science Symposium 2020. The 2020 meeting will be held virtually, November 14-16,  and will feature the most recent advances related to treating cardiopulmonary arrest and life-threatening traumatic injury.

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– Sudden Cardiac Arrest Foundation

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