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lifelines

Here are 28 public repositories matching this topic...

Python survival-analysis engine for retention strategy testing: K-Means personas, CoxPH runway modeling, high-risk scenario simulation, Kaplan-Meier curves, and executive PPTX/PDF outputs.

  • Updated May 30, 2026
  • Python

A biostatistical survival analysis pipeline using Python to evaluate patient prognosis in the Mayo Clinic PBC dataset. Implements Kaplan-Meier estimators and Cox Proportional Hazards models to mathematically process right-censored clinical data and identify mortality risk factors.

  • Updated Apr 8, 2026
  • Jupyter Notebook

Pancreatic Cancer Predictive Pipeline A professional clinical framework for pancreatic cancer prognosis. Combines Kaplan-Meier survival analysis and Cox Regression with an MLOps-powered machine learning pipeline (XGBoost/Random Forest) for real-time, high-recall patient risk stratification.

  • Updated Jun 23, 2026
  • Jupyter Notebook

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