Enriching patient populations in ICU trials: reducing heterogeneity through machine learning.
Journal:
Current opinion in critical care
Published Date:
May 2, 2025
Abstract
PURPOSE OF REVIEW: Despite the pivotal role of randomized controlled trials (RCTs) in critical care research, many have failed to demonstrate significant benefits, particularly in nutrition interventions. This review highlights how patient heterogeneity affects trial outcomes and explores how artificial intelligence and machine learning can address this issue by identifying subgroups with distinct treatment responses, improving trial design, and enhancing the precision of nutritional interventions.
