Survival analysis in Python

Machine Learning in R

Survival analysis built on top of scikit-learn

Survival analysis with PyTorch

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

Open source package for Survival Analysis modeling

Auton Survival - an open source package for Regression, Counterfactual Estimation, Evaluation and Phenotyping with Censored Time-to-Events

Improving XGBoost survival analysis with embeddings and debiased estimators

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

In this project, I have utilized survival analysis models to see how the likelihood of the customer churn changes over time and to calculate customer LTV. I have also implemented the Random Forest model to predict if a customer is going to churn and deployed a model using the flask web app.

This repository contains morden baysian statistics and deep learning based research articles , software for survival analysis

Code that might be useful to others for learning/demonstration purposes, specifically along the lines of modeling and various algorithms. **Superseded by the models-by-example repo**.

GPstuff - Gaussian process models for Bayesian analysis

Deep survival analysis made easy

A system for automating the design of predictive modeling pipelines tailored for clinical prognosis.

Datasets for Predictive Maintenance

Probabilistic Learning for mlr3

Deep Recurrent Survival Analysis, an auto-regressive deep model for time-to-event data analysis with censorship handling. An implementation of our AAAI 2019 paper and a benchmark for several (Python) implemented survival analysis methods.

Generates and evaluates D, I, A, Alias, E, T, G, and custom optimal designs. Supports generation and evaluation of mixture and split/split-split/N-split plot designs. Includes parametric and Monte Carlo power evaluation functions. Provides a framework to evaluate power using functions provided in other packages or written by the user.

Explainable Machine Learning in Survival Analysis