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Source codes of Stratified Interpretable Linear Model

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SLIM Codes

  1. Data Loading.py
  • Loading MAGGIC data from original csv file
  • Labeling for each patient
  • Divide them into train/test sets
  1. Prediction_Result.py
  • Using multiple machine learning methods to compute the prediction accuracy
  • With AUROC, AUPRC, and C-index as metrics
  1. RMSE_Compute.py
  • Report RMSE and Kappa of SLIM model
  • For each risk strata and entire strata
  1. Final_SettingA.py
  • Implement SLIM Model
  1. Calibration_Plot.py
  • Visualize Calibration of ML Models
  1. Coefficient_Heatmap.py
  • Compute coefficient of each risk strate to visualize Heatmaps

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Source codes of Stratified Interpretable Linear Model

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