sunnyadn/comprisk
Python toolkit for competing risks: forest (RSF) today; Fine-Gray + Aalen-Johansen + Gray's test + cause-specific Cox in v0.4. Scales to n=10⁶ in ~1 min, 10–22× faster than randomForestSRC on real EHR data, sklearn-compatible.
GitHub repository with 5 stars and 0 forks.
Language: Python
Topics: biostatistics, competing-risks, machine-learning, numba, python, random-forest, random-survival-forest, scikit-learn, survival-analysis