Explainable Machine Learning in Survival Analysis

COX Proportional risk model and survival analysis implemented by tensorflow.

Python/R library for feature selection in neural nets. ("Feature selection using Stochastic Gates", ICML 2020)

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

By-hand code for models and algorithms. An update to the 'Miscellaneous-R-Code' repo.

Code for the paper "Deep Cox Mixtures for Survival Regression", Machine Learning for Healthcare Conference 2021

Easily Process a Batch of Cox Models

Integrative Survival Models

Dynamic Models for Survival Data

Solution that I provided to the 2020 challenge organized by Collège de France and Ecole Normale Supérieure of Paris. I finished 2nd out of the 98 teams/participants that participated.

Survival Analysis of Lung Cancer Patients

Survival modelling using Cox proportional hazard regression model

Survival analysis functions that allow left truncation and weighting, including Aalen-Johansen, Kaplan-Meier, and Cox proportional hazards regression

Multiresponse time-to-event Cox proportional hazards model - CPU

Survival functions (client side) for DataSHIELD. Package for building survival models, Cox proportional hazards models and Cox regression models in DataSHIELD.

Interaction-Partitioned Topic Models (IPTM) using a Point Process Approach

Code and supplementary materials for the manuscript "Multiple imputation for cause-specific Cox models: assessing methods for estimation and prediction" (2022, Statistical Methods in Medical Research)

Smooth Hazard Ratio Curves Taking a Reference Value

Code and supplementary materials for the manuscript "Handling missing covariate data in clinical studies in haematology" (2023, Best Practice & Research Clinical Haematology)

simulated data and estimation code for replication purposes for the paper MKSC-20-0420