Survival Analysis With CatBoost

This repository contains a comprehensive survival analysis project focusing on mortality prediction and waitlist analysis in healthcare. The project utilizes various machine learning techniques, including CatBoost, XGBoost, and Random Forest models, to analyze and predict patient outcomes.

Project Structure

graph LR
  A[survival_analysis] --> B[final_model]
  B --> B1[survival_analysis_final_catboost_model.qmd]
  B --> B2[survival_analysis_final_catboost_model.html]
  B --> B3[stratified_risk_metrics.csv]
  B --> B4[sorted_shap_values_interactive.html]
  B --> C[images]
  C --> C1[catboost_beeswarm.png]
  C --> C2[mean_absolute_shap_importance.png]
  C --> C3[partial_dependence_plots_test]
  C --> C4[partial_dependence_plots_train]
  C --> C5[shap_correlation_plot.png]
  C --> C6[shapley_bar_one_hot.png]
  A --> D[tripod_ai_checklist]
  D --> D1[tripod_ai_checklistt.qmd]
  D --> D2[tripod_ai_checklist.html]
  A --> E[utilities]
  E --> E1[make.R]
  E --> E2[plotting.R]
  A --> F[model_data]
  F --> F1[center-stats.qmd]
  F --> F2[center-stats.html]
  F --> F3[model_data.qmd]
  F --> F4[model_data.html]
  F --> F5[waitlist-data2.qmd]
  F --> F6[waitlist-data2.html]
  A --> G[eda]
  G --> G1[listing-mortality-prediction.qmd]
  G --> G2[listing-mortality-prediction.html]
  G --> G3[survival_analysis_catboost_xgboost_random_forest.qmd]
  G --> G4[survival_analysis_feature_analysis.qmd]
  G --> G5[survival_analysis_feature_encoding.qmd]
  G --> G6[survival_analysis_model_evaluation.qmd]
  G --> G7[survival_analysis_models.qmd]

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Project Components

Final Model

The final_model/ directory contains- survival_analysis_final_catboost_model.qmd: The final CatBoost model for survival analysis. survival_analysis_final_catboost_model.qmd

Shap Values

The shap_values/ directory contains an Interactive Feature Importance Plot

Images

The images/ directory stores generated plots and figures:

• CatBoost beeswarm plot
• Mean absolute SHAP importance
• Partial dependence plots - Test and Train
• SHAP correlation plot
• Shapley bar plot (one-hot encoded)

TRIPOD+AI Checklist

The tripod_ai_checklist/ directory contains the completed TRIPOD+AI Checklist.

Model Data

The model_data/ directory contains the data pre-processing and processing used in the analysis.

Data

The data/ directory contains the data sets used in the analysis. Available upon request.

Exploratory Data Analysis (EDA)

The eda/ directory contains various aspects of the analysis:

• Center statistics
• Listing mortality prediction
• Comparison of CatBoost, XGBoost, and Random Forest models
• Feature analysis and encoding
• Model evaluation
• Waitlist data analysis

Utilities

The utilities/ directory contains R scripts for common functions:

• plotting.R: Custom plotting functions for the project
• 'make.R': Orchestration file for data pipelines

Usage

To reproduce the analysis:

1. Ensure you have R and the required packages installed.
2. Request the data files and place in /data directory.
3. Run survival_analysis_final_catboost_model.qmd.

Contact

Jerome Dixon