4 citations · 4 across the 3 of their papers we have counts for
3 papers
cs.LG2024
DNAMite: Interpretable Calibrated Survival Analysis with Discretized Additive Models
Mike Van Ness, Billy Block, Madeleine Udell
Survival analysis is a classic problem in statistics with important applications in healthcare. Most machine learning models for survival analysis are black-box models, limiting th…
cs.LG2024
Interpretable Prediction and Feature Selection for Survival Analysis
Mike Van Ness, Madeleine Udell
Survival analysis is widely used as a technique to model time-to-event data when some data is censored, particularly in healthcare for predicting future patient risk. In such setti…
cs.LG2023★ 4 cited
Interpretable Survival Analysis for Heart Failure Risk Prediction
Mike Van Ness, Tomas Bosschieter, Natasha Din +3
Survival analysis, or time-to-event analysis, is an important and widespread problem in healthcare research. Medical research has traditionally relied on Cox models for survival an…