Machine Learning Programs Predict Risk of Death Based on Results From Routine Hospital Tests - Neuroscience News

Summary: Using ECG data, a new machine learning algorithm was able to predict death within 5 years of a patient being admitted to hospital with 87% accuracy. The AI was able to sort patients into 5 categories ranging from low to high risk of death. If you've ever been admitted to hospital or visited an emergency department, you've likely had an electrocardiogram, or ECG, a standard test involving tiny electrodes taped to your chest that checks your heart's rhythm and electrical activity. Hospital ECGs are usually read by a doctor or nurse at your bedside, but now researchers are using artificial intelligence to glean even more information from those results to improve your care and the health-care system all at once. In recently published findings, the research team built and trained machine learning programs based on 1.6 million ECGs done on 244,077 patients in northern Alberta between 2007 and 2020.