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.

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)

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

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