Machine Learning Model Improves Mi Diagnosis

In a new study, a machine learning model that incorporates information from a single troponin test as well as other clinical data was found to be superior to current practice as an aid to the diagnosis of myocardial infarction (MI) in the emergency department. The model could double the proportion of patients who are identified correctly as having a low probability of an MI on arrival to enable immediate discharge and free up space in the emergency department, as well as increase the proportion of patients who are correctly identified as at a high probability of having an MI. The study was published online in Nature Medicine on May 11.