Survival Analysis

This skill creates publication-ready clinical decision support documents for pharmaceutical research and medical guideline development. It generates patient cohort analyses with biomarker stratification, evidence-based treatment recommendations using GRADE methodology, and includes statistical analysis tools for survival curves, hazard ratios, and clinical outcome comparisons.

Comprehensive toolkit for survival analysis and time-to-event modeling in Python using scikit-survival. Use this skill when working with censored survival data, performing time-to-event analysis, fitting Cox models, Random Survival Forests, Gradient Boosting models, or Survival SVMs, evaluating survival predictions with concordance index or Brier score, handling competing risks, or implementing any survival analysis workflow with the scikit-survival library.