Julie Alberge

SurvICL: a Foundation Model for in-context Survival Analysis

Tabular foundation models (TFMs) now outperform gradient-boosted trees in classification and regression. Yet in survival analysis, which predicts when an event occurs from censored data, often on...

Survival Models: Proper Scoring Rule and Stochastic Optimization with Competing Risks

The Loss or the Architecture? What Matters in Survival Analysis with Competing Risks

Often, \emph{eg} in healthcare and predictive maintenance, what matters is which of several competing causes will strike first, and with what probability: survival analysis with competing risks....

Development and external validation of a lung cancer risk estimation tool using gradient-boosting

Lung cancer is a significant cause of mortality worldwide, emphasizing the importance of early detection for improved survival rates. In this study, we propose a machine learning (ML) tool trained...

On the calibration of survival models with competing risks

Survival analysis deals with modeling the time until an event occurs, and accurate probability estimates are crucial for decision-making, particularly in the competing-risks setting where multiple...