Michael S. Beattie

This paper develops an AutoML framework with explainable AI tools to identify hemodynamic predictors of spinal cord injury outcomes.

The paper introduces ODC-TBI, a platform for sharing preclinical TBI data, enabling big data analytics and machine learning to address heterogeneity in TBI research.

The paper identifies soluble TNF receptor 1 (sTNFR1) as a therapeutic target for spinal cord injury using multi-dimensional analysis of preclinical data.

The paper identifies 197 genes in peripheral blood cells whose expression correlates with acute spinal cord injury severity, achieving 72.7% accuracy in predicting injury grades.