Machine learning algorithm to predict mortality in heart failure patients

Researchers from the University of California San Diego developed a machine-learning model by training a boosted decision tree algorithm on de-identified electronic health records data of 5,822 hospitalized or ambulatory patients with heart failure from the University of California San Diego. This machine learning model is based on eight readily available variables. These include, diastolic … Continue reading Machine learning algorithm to predict mortality in heart failure patients