3 papers
cs.LG2025
Neural Diffusion Processes for Physically Interpretable Survival Prediction
Alessio Cristofoletto, Cesare Rollo, Giovanni Birolo +1
We introduce DeepFHT, a survival-analysis framework that couples deep neural networks with first hitting time (FHT) distributions from stochastic process theory. Time to event is r…
cs.LG2025
Beyond Cox Models: Assessing the Performance of Machine-Learning Methods in Non-Proportional Hazards and Non-Linear Survival Analysis
Ivan Rossi, Flavio Sartori, Cesare Rollo +3
Survival analysis often relies on Cox models, assuming both linearity and proportional hazards (PH). This study evaluates machine and deep learning methods that relax these constra…
q-bio.QM2025
SurvHive: a package to consistently access multiple survival-analysis packages
Giovanni Birolo, Ivan Rossi, Flavio Sartori +3
Survival analysis, a foundational tool for modeling time-to-event data, has seen growing integration with machine learning (ML) approaches to handle the complexities of censored da…