Does including machine learning predictions in ALS clinical trial analysis improve statistical power?
Journal:
Annals of clinical and translational neurology
PMID:
32862509
Abstract
OBJECTIVE: Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease which leads to progressive muscle weakness and eventually death. The increasing availability of large ALS clinical trial datasets have generated much interest in developing predictive models for disease progression. However, the utility of predictive modeling on clinical trial analysis has not been thoroughly evaluated.