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

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

Explainable Machine Learning in Survival Analysis

Datasets for Predictive Maintenance

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

Survival analysis in Julia

Tutorial on survival analysis using TensorFlow.

Perform a survival analysis based on the time-to-event (death event) for the subjects. Compare machine learning models to assess the likelihood of a death by heart failure condition. This can be used to help hospitals in assessing the severity of patients with cardiovascular diseases and heart failure condition.

ICML 2018: "Adversarial Time-to-Event Modeling"

SurvTRACE: Transformers for Survival Analysis with Competing Events

A survival analysis interface for Julia

A probabilistic model to cluster survival data in a variational deep clustering setting

ML Approaches for RUL Prediction, Anomaly Detection, Survival Analysis and Failure Classification

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

R package for fitting joint models to time-to-event and longitudinal data

ProFeld: survival analysis, predictive maintenance, churn analysis, and remaining useful life prediction in Python

ACM CHIL 2020: "Survival Cluster Analysis"

Event Prediction in Clinical Trials with Time-to-Event Outcomes

Analysis of Multivariate Event Times https://kkholst.github.io/mets/

ACM CHIL 2021: "Enabling Counterfactual Survival Analysis with Balanced Representations"