Back to projects

StratifyML — Hospital Analytics for Vulnerable Populations

View resource →

  • data science
  • healthcare
  • frequent itemset mining
  • pandas

What it is

An analysis pipeline that studies hospital utilization across 13 vulnerable population groups (e.g. homeless, Medicaid, uninsured, elderly, rural).

It builds vulnerability flags, computes the Charlson Comorbidity Index from ICD-10 codes, then runs frequent-itemset mining (Apriori) over CPT/ICD code combinations and links those patterns to outcomes — length of stay, total charges, and mortality. Outputs publication-ready figures, LaTeX/CSV tables, and Excel reports highlighting health disparities.

Stack

Python · pandas · mlxtend (Apriori) · matplotlib/seaborn · networkx

Links