Survival Analysis Python Packages

lifelines

Survival analysis in Python

reliability

Reliability engineering toolkit for Python - https://reliability.readthedocs.io/en/latest/

scikit-survival

Survival analysis built on top of scikit-learn

skpro

A unified framework for tabular probabilistic regression, time-to-event prediction, and probability distributions in python

pycox

Survival analysis with PyTorch

surpyval

A Python package for survival analysis. The most flexible survival analysis package available. SurPyval can work with arbitrary combinations of observed, censored, and truncated data. SurPyval can also fit distributions with 'offsets' with ease, for example the three parameter Weibull distribution.

xgbse

Improving XGBoost survival analysis with embeddings and debiased estimators

torchsurv

Deep survival analysis made easy

survivaleval

The most comprehensive Python package for evaluating survival analysis models.

predictr

Weibull Analysis Tools

orange3-survival-analysis

🍊 :heavy_plus_sign: Survival Analysis add-on for Orange3 data mining suite.

pyicare

A Python distribution of iCARE, a tool for individualized Coherent Absolute Risk Estimation.

comprisk

Scalable, scikit-learn-compatible competing-risks survival analysis in pure Python — CR random survival forest, Fine-Gray, cause-specific Cox, Aalen-Johansen CIF, Gray's test, and exact TreeSHAP. 10–22× faster than randomForestSRC on real EHR and 16.6–544× vs scikit-survival (n=5k→50k); scales to n=10⁶ in ~1 min.

fracability

Analyse fracture networks for digitalized rock outcrops.

survival-datasets

Common datasets in survival analysis.

bess

Best Subset Selection algorithm for Regression, Classification, Count, Survival analysis

survshap

SurvSHAP(t): Time-dependent explanations of machine learning survival models

kaplanmeier

Create survival curves using kaplanmeier, the log-rank test and making plots.

random-survival-forest

A Random Survival Forest implementation for python inspired by Ishwaran et al. - Easily understandable, adaptable and extendable.

fife

Finite-Interval Forecasting Engine: Machine learning models for discrete-time survival analysis and multivariate time series forecasting

schneiderkamplab-xgbse

Improving XGBoost survival analysis with embeddings and debiased estimators

crforest

DEPRECATED — renamed to 'comprisk' in 0.3.1. Install `pip install comprisk`.

insurance-survival

Survival analysis for UK insurance pricing: cure models, competing risks, recurrent events, CLV, lapse tables, coherent cause-specific mortality, proper scoring rules. Extends lifelines with insurance-specific gaps.

survive

Survival analysis in Python