Interpretable Machine Learning for Survival Analysis

15 March 2024

Papers citing "Interpretable Machine Learning for Survival Analysis"

6 / 6 papers shown

Title
A Comparative Study of Methods for Estimating Conditional Shapley Values and When to Use Them Lars Henry Berge Olsen I. Glad Martin Jullum K. Aas FAtt 33 12 0 16 May 2023
Conditional Feature Importance for Mixed Data Kristin Blesch David S. Watson Marvin N. Wright 35 7 0 06 Oct 2022
SurvTRACE: Transformers for Survival Analysis with Competing Events Zifeng Wang Jimeng Sun 30 67 0 02 Oct 2021
SurvNAM: The machine learning survival model explanation Lev V. Utkin Egor D. Satyukov A. Konstantinov AAML FAtt 31 28 0 18 Apr 2021
SurvLIME: A method for explaining machine learning survival models M. Kovalev Lev V. Utkin E. Kasimov 98 89 0 18 Mar 2020
DeepSurv: Personalized Treatment Recommender System Using A Cox Proportional Hazards Deep Neural Network Jared Katzman Uri Shaham Jonathan Bates A. Cloninger Tingting Jiang Y. Kluger BDL CML OOD 102 1,229 0 02 Jun 2016