Ed Barbour

Ed Barbour


Areas of Interest

I continue to focus heavily in the Translational Research space. Currently I am engaged in machine learning of longitudinal demographic, steroidal, hormonal, and immunological variables (features) of rheumatoid arthritis (RA) for data collected over a 20-year span. Cohort analysis consists of determining the most significant and predictive variables for RA subjects, non-RA controls, pre-RA males, pre-RA females, and menopausal females. Additionally, I have been designing a machine learning pipeline to predict patients with high probability of advancing to a heart failure (HF) diagnosis in the pre-clinical phase, months before the usual diagnosis, by combining numerous clinical variables with SNP variant data, collected from literature searches, pertaining to HF related co-morbid conditions.


  • B.S., Oakland University (Computer Science)
  • M.S., University of Michigan (Bioinformatics)