Does including machine learning predictions in ALS clinical trial analysis improve statistical power?

Predictive modeling approaches for ALSFRS-R are able to explain a moderate amount of variability in longitudinal change, which is improved by robust missing data handling for baseline characteristics. Including ALSFRS-R post-baseline model prediction results as a covariate in the model for primary analysis may increase power under moderate treatment effects.