Can Machine Learning Predict Atrial Fibrillation Readmissions? – IAM Network

A recent analysis in Health Services Research and Managerial Epidemiology suggests that machine learning can play a role in helping predict readmissions for atrial fibrillation (AFib). The authors used data from the 2013 Nationwide Readmissions Database on AFib, aiming to create risk prediction models and ultimately predict 90-day hospital readmission rates. The researchers employed multiple machine learning methods (k-Nearest Neighbors, Decision Tree, and Support Vector Machine) to determine variable importance. The average patient age was 64.9 years, with 62% of patients being male. The primary outcome of interest was 90-day hospital readmissions status.