Methodological Review of Classification Trees for Risk Stratification: An Application Example in the Obesity Paradox.
Journal:
Nutrients
Published Date:
May 31, 2025
Abstract
BACKGROUND: Classification trees (CTs) are widely used machine learning algorithms with growing applications in clinical research, especially for risk stratification. Their ability to generate interpretable decision rules makes them attractive to healthcare professionals. This review provides an accessible yet rigorous overview of CT methodology for clinicians, highlighting their utility through a case study addressing the "obesity paradox" in critically ill patients.