55 citations · 56 across the 2 of their papers we have counts for
3 papers
What if we had built a prediction model with a survival super learner instead of a Cox model 10 years ago?
Arthur Chatton, Émilie Pilote, Kevin Assob Feugo +3
Objective: This study sought to compare the drop in predictive performance over time according to the modeling approach (regression versus machine learning) used to build a kidney…
Learning to rank for censored survival data
Margaux Luck, Tristan Sylvain, Joseph Paul Cohen +3
Survival analysis is a type of semi-supervised ranking task where the target output (the survival time) is often right-censored. Utilizing this information is a challenge because i…
Deep Learning for Patient-Specific Kidney Graft Survival Analysis
Margaux Luck, Tristan Sylvain, Héloïse Cardinal +2
An accurate model of patient-specific kidney graft survival distributions can help to improve shared-decision making in the treatment and care of patients. In this paper, we propos…