Developed a supervised classification model to predict admission type (in-patient vs out-patient) from electronic health record data using clinical lab results and vital signs.

  • Tools: Python, scikit-learn, pandas, matplotlib
  • Methods: Feature engineering from EHR data, logistic regression, random forest, model evaluation and comparison
  • Highlights: Built end-to-end classification pipeline; feature importance analysis for clinical interpretability
  • GitHub: View Repository