Comparison between neural networks and multiple logistic regression to predict acute coronary syndrome in the emergency room

摘要

ObjectivePatients with suspicion of acute coronary syndrome (ACS) are difficult to diagnose and they represent a very heterogeneous group. Some require immediate treatment while others, with only minor disorders, may be sent home. Detecting ACS patients using a machine learning approach would be advantageous in many situations.