Predicting Mortality Risk with Machine Learning from Routine Hospital Tests.
Originally Published 2 years ago — by Neuroscience News
Researchers have developed a machine learning algorithm that can predict the risk of death within one month, one year, and five years of a patient being admitted to the hospital with an 85% accuracy rate, using ECG data and demographic information. The algorithm sorts patients into five categories from lowest to highest risk. The study is a proof-of-concept for using routinely collected data to improve individual care and allow the health-care system to "learn" as it goes.